CBMF 4761
All COMS 42xx courses CSOR 4246
CSOR 4231
Further details about doctoral course requirements are posted here .
In addition to the four distribution courses, doctoral students must complete six elective graduate lecture courses approved by the student’s advisor. Additional courses from the approved lists, beyond the four needed to satisfy the distribution requirement, may be taken as electives. Most other graduate lecture courses offered by the Computer Science Department (or offered by Computer Science jointly with other departments) may be taken as electives, including 4995 and 6998 topics courses. At most two of the six electives may be graduate lecture courses offered by other departments besides Computer Science. Further details about course requirements are posted here .
All DES students and most PhD students arrange a research advisor during the admissions process prior to enrollment, and work closely with him or her on directed research from their first day in the program. Some doctoral students have two or more co-advisors. Almost all doctoral research advisors are tenured or tenure-track faculty members in the Computer Science Department. But in rare cases a PhD student’s research may be advised by a research scientist or an affiliated faculty member from another department, in which case the PhD student must also have a departmental advisor who is a tenured or tenure-track faculty member in Computer Science. The departmental advisor is responsible for tracking the student’s progress through doctoral program milestones, but is not responsible for the student’s research or funding. Both advisors are expected to represent their students at the Semi-Annual Review of all doctoral students held near the end of the fall and spring semesters. Further details on the department’s advising policy and Semi-Annual Review are posted here .
The primary focus of our doctoral program is research, with the philosophy that students learn best by doing – beginning as apprentices and becoming junior colleagues working with faculty on scholarly research projects. All PhD and DES students are required to conduct productive research under the direction of their advisor throughout the program. For PhD students, this should be half-time until completion of the coursework, teaching and candidacy exam requirements, and thereafter full-time until distribution of the dissertation. PhD s tudents are also expected to participate in departmental and laboratory activities throughout all fall and spring semesters of the program. The policy on outside activities by PhD students is here .
The directed research requirement is indeed a requirement , never waived, regardless of funding source, including employer-supported DES students. Insufficient or inadequate research progress is deemed unsatisfactory progress: the doctoral student is normally placed on probation and can be immediately dismissed from the program. However, on appeal of the student’s advisor, one semester’s grace can be granted by the full faculty.
The candidacy exam is an oral exam based on a syllabus prepared jointly by the student and his/her candidacy committee. Admission to candidacy (i.e., passing the exam) certifies that the student has demonstrated a depth of scholarship in the literature and the methods of the student’s chosen area of research, and has demonstrated a facility with the scholarly skills of critical evaluation and verbal expression. The candidacy exam should be completed by the end of the sixth semester or earlier, typically the semester after completing all courses, and must be completed prior to the thesis proposal. More detailed information, including the permitted composition of the candidacy committee, is here .
Doctoral students are required to register at least two weeks in advance for their Candidacy Exam using the department’s Doctoral Program Milestones Registration Form . Contact the PhD Program Administrator with any questions about the registration form.
In the thesis proposal, the student lays out his or her intended course of research for the dissertation. If the student passes the written and oral components of the proposal, the thesis proposal committee signs a form to recommend that the candidate proceed. The proposal should be completed by the end of the eighth semester. The university’s permitted composition of the dissertation prospectus committee and other requirements for the proposal are specified here . Additional department-specific requirements are here .
Doctoral students are required to register at least two weeks in advance for their Thesis Proposal using the department’s Doctoral Program Milestones Registration Form . Contact the PhD Program Administrator with any questions about the registration form.
The doctoral dissertation and defense is typically completed during the fifth or sixth year in the program. Some very highly motivated students, particularly in theoretical areas, may finish in less time.
Various forms and instructions for filling out the forms, composition of the dissertation committee, handling of remote participants in the defense, revision and deposit of the dissertation, and many other topics, are available from the GSAS Dissertation Office . Dissertation formatting requirements, including a latex template, are here . It’s particularly important for both the student and the advisor to review the university’s detailed requirements here about forming the dissertation committee, distributing the dissertation, and scheduling the defense.
Defenses are typically accompanied by a public seminar. In CS, we always hold that public seminar immediately before the defense. When a student schedules their “defense”, they should schedule enough time (~2 hours) for both that public seminar and the official defense. The department’s Doctoral Program Milestones Registration Form and the university’s Application for the Dissertation Defense form for PhD ( Application for the degree of Doctor of Engineering Science for DES) must be submitted by the student to the department’s PhD Program Administrator at least six weeks in advance of the anticipated defense date.
All doctoral students are required to fulfill two “teaching units”, ideally approximately the total workload of half-time for one semester, but the actual workload may vary widely. Both teaching units must be for courses approved by the department’s Academic Committee as Computer Science courses, where the CS department is responsible for staffing ( assigning Instruction assistants ), and occur during a regular academic semester while the student is enrolled in the doctoral program. Most students complete their teaching units during their second or third year, but there are no timing restrictions on which semesters (prior to MPhil ) students can do their teaching units. When students complete their teaching units is determined by their advisor. More detailed information is here .
The Department of Computer Science takes pride in maintaining a well-developed sense of community, and sees as an essential part of its doctoral program the preparation of its students for this important aspect of their future careers. It therefore strongly encourages students to contribute a year of service to the department’s professional, operational, or social needs, preferably during their second and/or third year in the program. A list of community service positions normally held by doctoral students is available in mice .
The en-course degree of Master of Philosophy is conferred upon a PhD student who has satisfactorily fulfilled all milestones except the proposal and dissertation. This includes all courses, teaching, and candidacy exam. The MPhil also requires completion of six Residency Units (RUs) and sixty graduate points beyond the undergraduate degree. Two RUs and thirty points of advanced standing are granted for completing the masters degree. See the university requirements for the MPhil .
Last updated August 16, 2024.
Find open faculty positions here .
Upcoming events, ms new student reception.
Tuesday 2:00 pm
Monday 9:00 am
Tuesday 9:00 am
Thursday 12:00 pm
Press mentions, dean boyce's statement on amicus brief filed by president bollinger.
President Bollinger announced that Columbia University along with many other academic institutions (sixteen, including all Ivy League universities) filed an amicus brief in the U.S. District Court for the Eastern District of New York challenging the Executive Order regarding immigrants from seven designated countries and refugees. Among other things, the brief asserts that “safety and security concerns can be addressed in a manner that is consistent with the values America has always stood for, including the free flow of ideas and people across borders and the welcoming of immigrants to our universities.”
This recent action provides a moment for us to collectively reflect on our community within Columbia Engineering and the importance of our commitment to maintaining an open and welcoming community for all students, faculty, researchers and administrative staff. As a School of Engineering and Applied Science, we are fortunate to attract students and faculty from diverse backgrounds, from across the country, and from around the world. It is a great benefit to be able to gather engineers and scientists of so many different perspectives and talents – all with a commitment to learning, a focus on pushing the frontiers of knowledge and discovery, and with a passion for translating our work to impact humanity.
I am proud of our community, and wish to take this opportunity to reinforce our collective commitment to maintaining an open and collegial environment. We are fortunate to have the privilege to learn from one another, and to study, work, and live together in such a dynamic and vibrant place as Columbia.
Mary C. Boyce Dean of Engineering Morris A. and Alma Schapiro Professor
Alternatively, use our A–Z index
Attend an open day
Discover more about postgraduate research
Year of entry: 2024
The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in a discipline directly relevant to the PhD (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD (or international equivalent).
Other combinations of qualifications and research or work experience may also be considered. Please contact the admissions team to check.
Full entry requirements
Apply online
In your application you’ll need to include:
Find out how this programme aligns to the UN Sustainable Development Goals , including learning which relates to:
Goal 8: decent work and economic growth, goal 9: industry, innovation and infrastructure, goal 17: partnerships for the goals, programme options.
Full-time | Part-time | Full-time distance learning | Part-time distance learning | |
---|---|---|---|---|
PhD | Y | Y | N | N |
Please enable JavaScript to watch this video.
The PhD is a three-year (or six year, if taken part-time) degree resulting in a substantial thesis.
The Department of Computer Science is one of the largest in the UK covering a huge spectrum of Computer Science topics. We currently have research groups ranging from Advanced Processor Technologies to Text Mining.
Our core Computer Science research is augmented by interdisciplinary research taking place at the interface with discipline areas including mathematics, physics, medicine and biology.
A detailed overview of the Department's research groups and core and interdisciplinary research themes is available in the 'research' area of our website and you can identify a possible project from our list of available projects .
For entry in the academic year beginning September 2024, the tuition fees are as follows:
Further information for EU students can be found on our dedicated EU page.
The programme fee will vary depending on the cost of running the project. Fees quoted are fully inclusive and, therefore, you will not be required to pay any additional bench fees or administration costs.
All fees for entry will be subject to yearly review and incremental rises per annum are also likely over the duration of the course for Home students (fees are typically fixed for International students, for the course duration at the year of entry). For general fees information please visit the postgraduate fees page .
Always contact the Admissions team if you are unsure which fees apply to your project.
There are a range of scholarships, studentships and awards at university, faculty and department level to support both UK and overseas postgraduate researchers.
To be considered for many of our scholarships, you’ll need to be nominated by your proposed supervisor. Therefore, we’d highly recommend you discuss potential sources of funding with your supervisor first, so they can advise on your suitability and make sure you meet nomination deadlines.
For more information about our scholarships, visit our funding page or use our funding database to search for scholarships, studentships and awards you may be eligible for.
The 17 United Nations Sustainable Development Goals (SDGs) are the world's call to action on the most pressing challenges facing humanity. At The University of Manchester, we address the SDGs through our research and particularly in partnership with our students.
Led by our innovative research, our teaching ensures that all our graduates are empowered, inspired and equipped to address the key socio-political and environmental challenges facing the world.
To illustrate how our teaching will empower you as a change maker, we've highlighted the key SDGs that our programmes address.
Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Strengthen the means of implementation and revitalize the Global Partnership for Sustainable Development
The School of Engineering creates a world of possibilities for students pursuing skills and understanding. Through dynamic research and teaching we develop engineering solutions that make a difference to society in an ethical and sustainable way. Science-based engineering is at the heart of what we do, and through collaboration we support the engineers and scientists of tomorrow to become technically strong, analytically innovative and creative. Find out more about Science and Engineering at Manchester .
Use the links below to view lists of programmes in related subject areas.
The University of Manchester is regulated by the Office for Students (OfS). The OfS aims to help students succeed in Higher Education by ensuring they receive excellent information and guidance, get high quality education that prepares them for the future and by protecting their interests. More information can be found at the OfS website .
You can find regulations and policies relating to student life at The University of Manchester, including our Degree Regulations and Complaints Procedure, on our regulations website .
Department of Computer Science
University | A to Z | Departments
Computer Science
You will be based in the Department of Computer Science overlooking the lake on Campus East .
You will benefit from modern offices and collaboration spaces, and well-equipped research labs with a specialist in-department team to support your requirements throughout your studies.
We will provide you with a laptop connected to the University network, and you will have 24/7 access to your desk and workspace. Distance learning students are allocated a work desk for the duration of their stay while they are in York.
For on-campus researchers, most of your training and supervision meetings will take place on campus at the University of York, though your research may take you further afield.
We offer the opportunity to study for a PhD by distance learning. This is available to students based in the UK and abroad, studying full-time or part-time. Our PhD by distance learning offers the same high quality of supervisory support (primarily online), and demands the same level of academic rigour as a campus-based PhD.
You will undertake your research and thesis production remotely, joining us on campus only occasionally. You will be expected to visit York at your own expense at the following stages of your study:
When you are not in York, you will continue to benefit from regular supervision meetings using online communication platforms, such as Zoom. Read more about how we support distance learners .
Are you an international applicant? It is important for you to note that it is your responsibility to meet any requirements for legal entry into the UK at the time of each of your visits. While the University and Department can provide supporting letters, the University cannot make any guarantees regarding entry visas or legal residence. Read more about applying for a visa.
Undergraduate and masters degrees.
The PhD in Computer Science is intended for students who already have a good first degree in Computer Science or a related field.
For entry to the PhD programme, we require at least a 2:1 undergraduate degree, or a qualification equivalent to a UK Masters degree with a minimum average grade of 60%.
We are willing to consider your application if you do not fit this profile, providing you are able to demonstrate that you have the required amount of Computer Science knowledge and experience to succeed on the programme.
If English is not your first language you must provide evidence of your ability.
Find out more about English Language requirements for research degrees
Find a potential supervisor.
You should find a potential supervisor in our Department whose area of research overlaps with yours. We encourage you to contact them to discuss your research proposal before you apply. Please identify the name of your potential supervisor in your application.
On our Research web pages, you can explore our research groups which reflect the core research strengths and expertise within the Department of Computer Science. On the web page for each research group, you'll find more information about the aims and objectives of the group and the names of group members. You can use this information to identify the groups where research interests match your own.
If you have any questions or need further information, please contact [email protected] .
We require you to submit the following documents:
Your research proposal needs to outline the nature of your proposed study and give some indication of how you will conduct your research. The purpose of this exercise is to ensure that you and your potential supervisor(s) have matching research interests.
Your proposal can build on your chosen supervisor's area of work and may be prepared with the help of your chosen supervisor. It should be about 500 to 1,000 words in length, in English and in your own words. Read more about writing a research proposal .
You can apply and send all your documentation electronically through our online system. You don’t need to complete your application all at once: you can start it, save it and finish it later.
After you have applied, you can track the status of your application and view any official correspondence online. If you have applied for an advertised scholarship, decisions on funded places may take a little longer.
If we are impressed by your full application, personal statement and references, we will invite you to interview.
The interview panel will be made up of your potential supervisor(s) and another independent academic. During your interview, it is important that you demonstrate an understanding of your chosen topic and its supporting theories.
For students based outside the UK, interviews are held online via Zoom. Applicants based in the UK are offered the opportunity to attend their interview in York. If you choose to attend in person, your visit will include a tour of the Department and its facilities.
Related links Explore our PhD opportunities Research groups in the Department of Computer Science About our research degrees Applying for a research degree Funding for research degrees Information for International students Accommodation Life at York
Department of Computer Science Deramore Lane , University of York , Heslington , York , YO10 5GH , UK Tel: work 01904 325501
Legal statements | Privacy | Cookies | Accessibility © University of York | Modify | Direct Edit
Renee Whitmore
Editor-in-Chief
Share this on:
In this article, we will be covering…
You finished at least a bachelor’s in computer science, and maybe a master’s too.
Are you now deciding whether you should go back for your PhD in computer science? Getting a PhD is a big commitment, and you should be entirely sure you’re willing to put in the time and effort required to complete the degree. You’ll likely experience setbacks while working toward your PhD, but the rewards can make all the hard work worth it.
We are going to help you evaluate if its worth it to you to pursue a PhD in computer science in terms of the years you’ll have to invest, the kind of job you may end up working after graduation, and the salary you can expect once you land your dream job. Keep reading to learn more about the computer science field!
READ MORE: Ultimate Guide to Computer Science
The answer to this question completely depends on what you wish to accomplish by earning this degree. For some, getting their PhD comes down to the prestige associated with a doctorate degree and being the top-most authority in a particular subject. In contrast, others complete their PhD to land a specific job that requires the highest degree in the field.
You should also consider where you’re at in your life in order to determine whether or not you are willing to invest the vast amount and time and effort it requires to earn this degree. Those with a full-time job and a family may find that the time commitments are too extensive. And those who have recently graduated from a bachelor’s or master’s program and are eager to enter the workforce might think the same. A PhD in this field typically requires around four or five years of dedicated study, which is simply too daunting for some people.
READ MORE: Best Online Computer Science Degrees
Pretty much any job in the computer science field is open for those who have earned their PhD in computer science. Those with this doctoral degree are particularly suited and qualified to pursue a career as a postsecondary computer science teacher or as a computer and information research scientist.
While 47% of postsecondary computer science teachers only have a master’s degree, getting a PhD may help give you the advantage over other candidates when applying for jobs. Around 42% of postsecondary computer science teachers have doctorate degrees, which may indicate that the field is moving toward preferring candidates who have a doctorate.
As a computer and information research scientist, you can expect to spend your days solving complex computer hardware and software problems. In this career, you could be theorizing about potential computer system problems, as well as designing and inventing creative solutions to the problems The job has an excellent outlook, as between 2018 and 2028 the number of computer and information research scientists is expected to increase by 17% , which is much higher than the national average across all industries.
READ MORE: Best Online Master’s in Computer Science
How much you end up making after you graduate with your PhD in computer science largely depends on both the career you decide to pursue as well as where you live. Computer and information research scientists can expect to earn a median income of $118,370 per year. Salaries vary greatly between states, with the median income the highest in Washington at just under $140,000 annually and the lowest median income in West Virginia at $63,510 . It’s also worth noting that the salary numbers given are the median incomes, with many individuals making significantly more and less money each year.
If you decide to pursue a career as a postsecondary computer science teacher, you’ll likely earn around $82,220 per year. If you live in California or decide to move to that state as a postsecondary computer science teacher, expect to earn a median income of $125,900 yearly. Postsecondary computer science teachers in West Virginia, on the other hand, earn an annual median salary of $52,000 per year.
See Also: How Hard is it to Get a Job in Computer Science?
© Copyright 2024 Online Schools Report
Ph.D. in Computer Science
Credits: | ||
Theoretic Concepts in Computers and Computation | 3 | |
Selected topics in set theory, Boolean Algebra, graph theory, and combinatorics. Formal languages, regular expressions and grammars. Automata and Turing machines. Algorithms and computability. 3-0-3 | ||
Programming Languages | 3 | |
Co-requisite: CSCI 651 The general principles of modern programming language design: Imperative (as exemplified by Pascal, C and Ada), functional (Lisp), and logical (Prolog) languages. Data management, abstract data types, packages, and object-oriented languages (Ada, C + +). Control structures. Syntax and formal semantics. While some implementation techniques are mentioned, the primary thrust of the course is concerned with the abstract semantics of programming languages. 3-0-3 | ||
Algorithm Concepts | 3 | |
Abstract Data Structures are reviewed. The course covers the study of both the design and analysis of algorithms. Design methods include: divide-and-conquer; the greedy method; dynamic programming; basic traversal and search techniques algebraic and geometric problems as well as parallel algorithms (PRAM). Space and time complexity; performance evaluation; and NP-Hard and NP-Complete classes are also covered. The purpose of this approach to the subject is to enable students to design and analyze new algorithms for themselve. 3-0-3 | ||
Total: 9 Credits | ||
Electives can be selected from the following list in the areas of: Computer Science; Cybersecurity; and Data Science. | ||
Credits: | ||
Distributed Systems | 3 | |
This course introduces the principles and practice underlying the design of distributed systems, both Internet-based and otherwise. Major topics include interprocess communication and remote invocation, distributed naming, distributed file systems, data replication, distributed transaction mechanisms, and distributed shared objects, secure communication, authentication and access control, mobile code, transactions and persistent storage mechanisms. A course project is required to construct working distributed applications using contemporary languages, tools and environments. 3-0-3 | ||
Operating System Security | 3 | |
In this course students are introduced to advanced concepts in operating systems with emphasis on security. Students will study contemporary operating systems including UNIX and Windows. Topics include the application of policies for security administration, directory services, file system security, audit and logging, cryptographic enabled applications, cryptographic programming interfaces, and operating system integrity verification techniques. Equivalent to ITEC 445. 3-0-3 | ||
Information Retrieval | 3 | |
This course provides students with an introduction to the basics and techniques of information retrieval. Topics cover search engines, retrieval strategies such as vector space, extended Boolean, probabilistic models and evaluation methods including relevance-based measures, query processing, indexing and searching. Classroom Hours- Laboratory and/or Studio Hours- Course Credits: 3-0-3 3-0-3 | ||
Big Data Analytics | 3 | |
Organizations today are generating massive amounts of data that are too large and unstructured to fit in relational databases. Organizations and enterprises are turning to massively parallel computing solutions such as Hadoop. The Apache Hadoop platform allows for distributed processing of large data sets across clusters of computers using the map and reduce programming model. Students will gain an in-depth understanding of how MapReduce and Distributed File Systems work. In addition, they will be able to author Hadoop-based MapReduce applications in Java and use Hadoop subprojects Hive and Pig to build powerful data processing applications. Industry systems, such as IBM InfoSphere BigInsights and IBM InfoSphere Streams will be studied. Classroom Hours- Laboratory and/or Studio Hours- Course Credits: 3-0-3 3-0-3 | ||
Computer Architecture I | 3 | |
This course explores modem architectural design patterns and exposes the students to latest technologies used to build computing systems. Concepts presented in this course include but are not limited to pipelining, multicore processors, superscalar processors with in-order and out-of order execution, virtual machines, memory hierarchy, virtual memory, interconnection networking, storage and I/0 architectures, computer clustering and cloud computing. Students are introduced to performance evaluation techniques and learn how to use the results of such techniques in the design of computing systems. Equivalent to EENG 641. 3-0-3 | ||
Numerical Analysis | 3 | |
Real and complex zeros of a function and polynomials, interpolation, roundoff error, optimization techniques, least square techniques, orthogonal functions, Legendre and Chebyshev polynomials, numerical integration and differentiation, numerical solution of differential equations with initial and boundary values. The numerical methods developed will emphasize efficiency, accuracy and suitability to high-speed computing. Selected algorithms may be flowcharted and programmed for solution on a computer. 3-0-3 | ||
Database Interface and Programming | 3 | |
An advanced course in static and dynamic programming embedded SQL using C. Open Database Connectivity (ODBC), interface to access data from various database management systems with Structured Query Language (SQL). Classroom Hours- Laboratory and/or Studio Hours- Course Credits: 3-0-3 3-0-3 | ||
Principles of Information Security | 3 | |
In this course students will study the issues involved in structuring information systems to meet enterprise requirements including security and public policy regulations. Topics include the building blocks of an information system, emphasizing the security and administration aspects of each, as well as life- cycle considerations, and risk management. The course will also include a special project or paper as required and specified by the instructor and the SoECS graduate committee. Classroom Hours- Laboratory and/or Studio Hours- Course Credits 3-0-3 | ||
Automata Theory | 3 | |
Theory of finite automata, identification of states. Turing Machines, neural nets, majority logic. Applications in pattern recognition and game playing. Hardware and software implementations. 3-0-3 | ||
Distributed Database Systems | 3 | |
Concepts underlying distributed systems: synchronization, communication, fault-tolerance. Concepts and architecture of distributed database systems. Distributed concurrency control and recovery. Replicated databases. Distributed Query Processing. Examples of commercial relational distributed DBMS. Classroom Hours- Laboratory and/or Studio Hours- Course Credits: 3-0-3 3-0-3 | ||
Introduction to Data Mining | 3 | |
This course introduces the concepts, techniques, and applications of data mining. Topics include data preprocessing, clustering, data warehouse and Online Analytical Processing (OLAP) technology, cluster and social network analysis, data classification and prediction, multimedia and web mining. Classroom Hours- Laboratory and/or Studio Hours- Course Credits: 3-0-3 3-0-3 | ||
Software Engineering | 3 | |
Techniques for the development and implementation of high-quality digital computer software are presented. Major areas covered in the course include software quality factors and metrics, software development outlines and specification languages, top-down vs. bottom-up design and development, complexity, testing and software reliability. 3-0-3 | ||
Computer Networks | 3 | |
Connection of multiple systems in a networked environment. Topics include physical connection alternatives, error management at the physical level, commercially available protocol support, packet switching, LANs, WANs and Gateways. 3-0-3 | ||
Artificial Intelligence I | 3 | |
Prerequisite: CSCI 651 This course will cover machine learning (ML) concepts, decision theory, classification, clustering, feature selection, and feature extraction. Emphasis is on the core idea and optimization theory behind ML methods. Important ML applications (including biometrics and anomaly detection) will also be covered. 3-0-3 | ||
Database Systems | 3 | |
Prerequisites: CSCI 651 or DTSC 610 Design and implementation of databases. Hierarchal and network concepts; relational databases systems; entity relationship model: query languages; relational design theory; security and authorization; access methods; concurrency control backup and recovery. 3-0-3 | ||
Advanced Software Engineering | 3 | |
Prerequisite: CSCI 665 The major emphasis in this course is on the structural design of software. Methods and concepts covered include cohesion and coupling; structured and composite design: Jackson methodology; higher order software; data abstraction and design of program families. 3-0-3 | ||
Advanced Network and Internet Security | 3 | |
In this course, students are introduced to the design of secure computer networks. Exploitation of weaknesses in the design of network infrastructure and security flaws in network protocols are presented and discussed. Network operation systems and network architectures are reviewed, together with the respective security related issues. Issues related to the security of content and applications such as emails, DNS, web servers are also addressed. Security techniques including intrusion detection, forensics, cryptography, authentication and access control are analyzed. Security issues in IPSEC, SSL/ TLS and the SSH protocol are presented. 3-0-3 | ||
Computer Security Risk Management and Legal Issues | 3 | |
This course explores several domains in the Information Security Common Body of Knowledge. Students in this course will be introduced to the following domains within Information Security: Security Management Practices, Security Architecture and Models, Business Continuity Planning (BCP), Disaster Recovery Planning (DRP), Law, Investigations, Ethics, Physical Security, Operations Security, Access Control Systems and Methodology, Network and Internet Security. 3-0-3 | ||
Digital Forensics | 3 | |
Prerequisite: INCS 615 Digital forensics is concerned with the post-analysis of information systems that have already been compromised, usually by criminal actors. It is a field that encompasses a range of topics, including computer forensics, memory forensics, network forensics, and incident response. This course is an introduction to the investigation procedures that are used in digital forensics. These procedures, depending on the type of crime, reconstruct the events that led to the compromise. Students who take this course will gain an in depth understanding of handling digital evidence, gathering and investigating artifacts and evidence, and effectively managing security incidents, including incident response techniques for preventing and addressing cyberattacks. 3-0-3 | ||
Cryptography | 3 | |
In this course we introduce the students to key issues in cryptography. Topics covered include definitions of security, digital signatures, cryptographic hash functions, authentication, symmetric and asymmetric encryption, stream ciphers, and zero knowledge proof systems. 3-0-3 | ||
Intrusion Detection and Hacker Exploits | 3 | |
Prerequisite: CSCI 620 and INCS 615 Methods used in computer and network hacking are studied with the intention of learning how to better to protect systems from such intrusions. Methods used by hackers include reconnaissance techniques, system scanning, and gaining system access by network and application level attacks, and denial of service attacks. The course will extensively study Internet related protocols, methods of traffic analysis, tools and techniques for implementing traffic filtering and monitoring, and intrusion detection techniques. Students will study common hacking and evasion techniques for compromising intrusion detection systems. 3-0-3 | ||
Data Center Security | 3 | |
Prerequisite: INCS 745 Data Center Security is concerned with the study of computer architectures and systems that provide critical computing infrastructure. This infrastructure combines hardware devices including computers, firewalls, routers, switches, and software applications such as email systems, Web servers, and computer desktop operating systems, to implement and manage organization wide secure computing capability. Examples of critical systems include intranet, extranet, and Internet systems. 3-0-3 | ||
Programming for Data Science | 3 | |
This course will introduce basic programming concepts (i.e. in Python and R), and techniques including data structures (vector, matrix, list, data frame, factor), basic and common operations/concepts (indexing, vectorization, split, subset), data input and output, control structures and functions. Other topics will include string operations (stringr package) and data manipulation techniques (dplyr, reshape2 packages). The course will also explore data mining, such as probability basics/data exploration, clustering, regression, classification, graphics and debugging. 2-2-3 | ||
Optimization Methods for Data Science | 3 | |
Corequisites: DTSC 635 Basic concepts in optimization are introduced. Linear optimization (linear and integer programming) will be introduced including solution methods like simplex and the sensitivity analysis with applications to transportation, network optimization and task assignments. Unconstrained and constrained non-linear optimization will be studied and solution methods using tools like Matlab/Excel will be discussed. Extensions to game theory and computational methods to solve static, dynamic games will be provided. Decision theory algorithms and statistical data analysis tools (Z-test, t-test, F-test, Bayesian algorithms and Neyman Pearson methods) will be studied. Linear and non-linear regression techniques will be explored. 3-0-3 | ||
Statistics for Data Science | 3 | |
This course presents a range of methods in descriptive statistics, frequentist statistics, Bayesian statistics, hypothesis testing, and regression analysis. Topics includes point estimation, confidence interval estimation, nonparametric model estimation, parametric model estimation, Bayesian parametric models, Bayesian estimators, parametric testing, nonparametric testing, simple and multiple linear regression models, logistic regression model. 3-0-3 | ||
Data Visualization | 3 | |
This course is designed to provide an introduction to the fundamental principles of designing and building effective data visualizations. Students will learn about data visualization principles rooted in graphic design, psychology and cognitive science, and how to the use these principles in conjunction with state-of-the-art technology to create effective visualizations for any domain. Students who have taken this course will not only understand the current state-of-the-art in data visualization but they will be capable of extending it. 3-0-3 | ||
Probability and Stochastic Processes | 3 | |
This course starts with a review of the elements of probability theory such as: axioms of probability, conditional and independent probabilities, random variables, distribution functions, functions of random variables, statistical averages, and some well-known random variables such as Bernoulli, geometry, binomial, Pascal, Gaussian, and Poisson. The course introduces more advanced topics such as stochastic processes, stationary processes, correlations, statistical signal processing, and well-known processes such as Brownian motion, Poisson, Gaussian, and Markov. Prerequisite: Undergraduate level knowledge of probability theory. 3-0-3 | ||
Introduction to Big Data | 3 | |
Prerequisite: DTSC 610 This course provides an overview of big data applications ranging from data acquisition, storage, management, transfer, to analytics, with focus on the state-of-the-art technologies, tools, and platforms that constitute big-data computing solutions. Real-life big data applications and workflows are introduced as well as use cases to illustrate the development, deployment, and execution of a wide spectrum of emerging big-data solutions. 3-0-3 | ||
Machine Learning | 3 | |
Prerequisite: DTSC 615 In this course, students will learn important machine learning (ML) and data mining concepts and algorithms. Emphasis is on basic ideas and intuitions behind ML methods and their applications in activity recognition, and anomaly detection. This course will cover core ML topics such as classification, clustering, feature selection, Bayesian networks, and feature extraction. Classroom teaching will be augmented with experiments performed on machine learning systems. Student understanding and progress will be measured through quizzes, exams, homework, project assii.mments, proposals, term-paper reports, and presentations. 3-0-3 | ||
Deep Learning | 3 | |
Prerequisites: DTSC 620, DTSC 710 This course presents a range of topics from basic neural networks, convolutional and recurrent network structures, deep unsupervised and reinforcement learning, and applications to problem domains like speech recognition and computervision. Classroom Hours- Laboratory and/or Studio Hours- Course Credits: 3-0-3 3-0-3 | ||
Biometrics | 3 | |
Prerequisite: DTSC 710 Biometrics has emerged as an important tool for user identification and authentication in security-critical applications, both the physical and virtual world. At its core, biometrics is an application of machine learning and anomaly detection. This course introduces biometrics concepts by building on machine learning and anomaly detection, and shows how state-of-the-art machine learning techniques are currently applied to biometric authentication. The course covers core biometric topics, and discusses the innovations made in the past decade. The course also concentrates on emerging biometric applications and their privacy, security, and usability, implications in a networked society. 3-0-3 | ||
Total: 27 Credits | ||
** Students can register for the courses below multiple times with credits ranging from 1 to 9 to fulfill the total 30-credit requirement for research and dissertation. | ||
Credits: | ||
Independent Research** | 1–9 | |
This course is devoted to independent research for PhD student. Work is carried out under supervision of a graduate school faculty member and must be approved by the chairperson of ECE department. 0-0-1 | ||
Total: 18 Credits | ||
Credits: | ||
Ph.D. Dissertation** | 1–9 | |
Development and implementation of original research. After completion of preliminary dissertation proposal, candidates must continue to register for this course to maintain candidacy until the completed dissertation is submitted. 0-0-1 | ||
Total: 12 Credits | ||
Students will be required to maintain an overall GPA of 3.0 in Ph.D. courses. A grade below a B- will result in the student repeating the course. | ||
|
By continuing to use the website, you consent to analytics tracking per NYIT's Privacy Statement Accept Cookies
Explore Jobs
Find Specific Jobs
Explore Careers
Explore Professions
Best Companies
Explore Companies
This question is about computer scientist education .
How long does it take to get a Ph.D. in computer science?
It takes four to five years to get a Ph.D. in computer science. A doctorate in computer science builds upon a student's existing knowledge, skills, and experience in the field.
It involves independent research and study focused on a specific area of interest in computer science. Here is some more information on Ph.D. computer science programs:
Requirements. To get accepted into a doctorate computer science program, you must first obtain a bachelor's degree in computer science or another relevant area. Many programs also require you to obtain a master's degree in preparation. Candidates for these programs also often have to submit the following:
Letters of recommendation
Projects they have worked on or research they have engaged in
Bachelor's degree programs in computer science typically take four years to complete, while a master's program in the field can take one to two years. Obtaining a master's degree in computer science increases the chances a student will be accepted into a computer science doctorate program.
Specializations. Most candidates wanting to complete a computer science doctoral degree seek to specialize in the field or want to teach at the college level as a computer science professor.
All students must be able to show academic success in their previous educational programs and exhibit a desire to continue their learning and research in a Ph.D. program.
Ph.D. in computer science timeframe. A Ph.D. in computer science normally takes four to five years to complete. This breaks down into course credits ranging from 72 to 90 credits, diversifying Ph.D. programs in this field.
Many students choose to pursue interdisciplinary degrees in these programs. Students have the option to focus purely on computer science or one of the following areas:
Algorithms, combinatorics, and optimization
Human-computer interaction
Software engineering
Language and information technologies (IT)
Machine learning
Computational biology
Artificial intelligence (AI)
Related topics, related questions for computer scientist, recent job searches.
Learn more about computer scientist jobs.
Can you work from home with a computer science degree?
What do computer scientists do on a daily basis?
Are computer scientists happy?
How many hours do computer scientists work?
What is the highest-paying job in computer science?
Phd in computer science (2023 entry).
Course code
2 October 2023
3-4 years full-time; Up to 7 years part-time
Qualification
Computer Science
University of Warwick
The PhD in Computer Science offers exciting opportunities to do cutting-edge research in an internationally renowned environment. The results of the 2021 REF rank Warwick Computer Science 4th out of 90 UK Computer Science departments. This cements our position as one of the top Computer Science departments in the UK, a position we have held for some time under different assessment methodologies.
The PhD program is suitable for skilled and highly-motivated students to do research at the frontiers of Computer Science in a broad range of theoretical and applied topics. The program is meant to train students for high-profile jobs in both Academia and Industry.
General entry requirements, minimum requirements.
2:i undergraduate degree (or equivalent) and preferably an MSc in a related subject.
You can find out more about our English language requirements Link opens in a new window . This course requires the following:
English language requirements Band A IELTS overall score of 6.5, minimum component scores not below 6.0.
International Students
We welcome applications from students with other internationally recognised qualifications.
For more information please visit the international entry requirements page .
For more information, please visit the international entry requirements page Link opens in a new window .
There are no additional entry requirements for this course.
Research themes.
The current research themes include:
Full details on our current research is available on the Computer Science website. Link opens in a new window
Before you make a formal application, your proposal is emailed to a potential supervisor for their consideration. You may not be considered for a research degree if you do not have (and we could not identify) an academic willing to supervise your research.
Explore the research interests of our academic staff. Link opens in a new window
You can also see our general University guidance about finding a supervisor. Link opens in a new window
Tuition fees are payable for each year of your course at the start of the academic year, or at the start of your course, if later. Academic fees cover the cost of tuition, examinations and registration and some student amenities.
Taught course fees Research course fees
We carry out an initial fee status assessment based on the information you provide in your application. Students will be classified as Home or Overseas fee status. Your fee status determines tuition fees, and what financial support and scholarships may be available. If you receive an offer, your fee status will be clearly stated alongside the tuition fee information.
Do you need your fee classification to be reviewed?
If you believe that your fee status has been classified incorrectly, you can complete a fee status assessment questionnaire. Please follow the instructions in your offer information and provide the documents needed to reassess your status.
Find out more about how universities assess fee status
As well as tuition fees and living expenses, some courses may require you to cover the cost of field trips or costs associated with travel abroad. Information about department specific costs should be considered in conjunction with the more general costs below, such as:
As well as tuition fees and living expenses, some courses may require you to cover the cost of field trips or costs associated with travel abroad.
For departmental specific costs, please see the Modules tab on the course web page for the list of core and optional core modules with hyperlinks to our Module Catalogue (please visit the Department’s website if the Module Catalogue hyperlinks are not provided).
Associated costs can be found on the Study tab for each module listed in the Module Catalogue (please note most of the module content applies to 2022/23 year of study). Information about module department specific costs should be considered in conjunction with the more general costs below:
Find out about the different funding routes available, including; postgraduate loans, scholarships, fee awards and academic department bursaries.
Find out more about the various funding opportunities that are available in our department.
Find out more about the cost of living as a postgraduate student at the University of Warwick.
What are computers capable of? How do we use them to solve major world problems? What are their limitations?
Computer Science at Warwick offers you a community of excellence across the breadth of computer science. Join like-minded thinkers and friends who relish the challenges of shaping future technology.
You will study the theoretical foundation in established areas of the discipline. You will then apply your learning to industrially relevant problems, developing technical and transferable skills which will position you excellently for your future career.
Find out more about us on our website.
Here is our checklist on how to apply for taught postgraduate courses at Warwick.
Here is our checklist on how to apply for research postgraduate degrees at the University of Warwick.
Find out how we process your application.
Track your application and update your details.
See Warwick’s postgraduate admissions policy.
Ask questions and engage with Warwick.
Postgraduate fairs.
Throughout the year we attend exhibitions and fairs online and in the UK. These events give you the chance to learn about our Master's and PhD study routes, and the wider context of postgraduate study.
Find out more
Every week, you can connect directly with representatives from Warwick, who will be answering your questions on applying to and studying postgraduate studies at Warwick.
Sign up for Live Chats
Some academic departments hold events for specific postgraduate programmes, these are fantastic opportunities to learn more about Warwick and your chosen department and course.
See our online departmental events
Want to hear more about postgraduate study at Warwick? Register your interest and find out more.
Learn more about Postgraduate study at the University of Warwick.
Discover why Warwick is one of the best universities in the UK and renowned globally.
6th in the UK (The Guardian University Guide 2022) Link opens in a new window
64th in the world (QS World University Rankings 2023) Link opens in a new window
5th most targeted university by the UK's top 100 graduate employers Link opens in a new window
(The Graduate Market in 2023, High Fliers Research Ltd. Link opens in a new window )
This information is applicable for 2023 entry. Given the interval between the publication of courses and enrolment, some of the information may change. It is important to check our website before you apply. Please read our terms and conditions to find out more.
COMMENTS
The Computer Science Department PhD program is a top-ranked research-oriented program, typically completed in 5-6 years. There are very few course requirements and the emphasis is on preparation for a career in Computer Science research.
In theory, yes, it is possible. In practice it depends on many things. Let me try to list a bunch of the variables that have affect the time required. The minimum requirements that you are likely to find for a doctorate are (a) pass a set of qualifying exams and (b) write a dissertation acceptable to the faculty.
Interested in a computer science Ph.D. program? Use our guide to learn the benefits of pursuing this degree and what to expect.
Course Guidelines for Ph.D. Students in Computer Science We expect students to obtain broad knowledge of computer science by taking graduate level courses in a variety of sub-areas in computer science, such as systems, networking, databases, algorithms, complexity, hardware, human-computer interaction, graphics, or programming languages.
A Ph.D. in computer science is a doctoral degree that students can earn after completing advanced research on a complex computer science topic, such as artificial intelligence (AI) or network architecture. A doctorate is the highest academic degree students can earn in the computer science field. These programs typically teach students how to ...
The Computer Science Department also believes that teaching is an integral and important part of graduate-level education in Computer Science. In pursuing the PhD degree, students have clear and defined milestones that help guide them to the successful completion of their dissertation and oral defense. This includes a cumulative list of requirements to be completed in order for students to ...
We're thrilled that you are interested in our PhD program in computer science! This page provides an overview of the application process, some guidelines, and answers to specific questions.
The PhD is the Computer Science Department's primary doctoral program. PhD students are expected to be during every fall and spring academic semester from initial enrollment until the dissertation has been distributed to their defense committee, except during leaves of absence approved by the university. PhD students spend at least half of ...
The computer science Ph.D. program complies with the requirements of the Cornell Graduate School, which include requirements on residency, minimum grades, examinations, and dissertation. The Department also administers a very small 2-year Master of Science program (with thesis).
Doctoral Degree in Computer Science Carnegie Mellon's Ph.D. in Computer Science is, above all, a research degree. When the faculty award a Ph.D., they certify that the student has a broad foundation and awareness of core concepts in computer science, has advanced the field by performing significant original research and has reported that work in a scholarly fashion.
PhD in Computer Science The doctor of philosophy in computer science program at Northwestern University primarily prepares students to become expert independent researchers. PhD students conduct original transformational research in extant and emerging computer science topics. Students work alongside top researchers to advance the core CS fields from Theory to AI and Systems and Networking. In ...
A doctoral dissertation that demonstrates original and advanced research in computer science. Program Length: 4 years for PhD after a recognized Master's degree. 5 years for Direct Entry PhD after a Bachelor's degree. Guaranteed Funding Period: 43 months if master's degree was completed in this department.
Overview of the PhD Program For specific information on the Computer Science PhD program, see the navigation links to the right. What follows on this page is an overview of all Ph.D. programs at the School; additional information and guidance can be found on the Graduate Policies pages.
The PhD is the primary research degree that can be taken in the Department of Computer Science and Technology. The Cambridge PhD is a three to four-year full-time (five to seven-year part-time) programme of individual research on a topic agreed by the student and the Department, under the guidance of a staff member as the student's supervisor.
Kee says funding for a humanities Ph.D. program typically only lasts five years, even though it is uncommon for someone to obtain a Ph.D. degree in a humanities field within that time frame ...
Learn everything you need to know about getting an online PhD in Computer Science including salary, requirements, and how to get started.
Analysis of Algorithms is the core of Computer Science, which unites the many disparate subfields. All doctoral students are expected to complete an acceptable lecture course (graduate or upper-level undergraduate) in Analysis of Algorithms, with grade B+ or higher, prior to entering the program.
The PhD is a three-year (or six year, if taken part-time) degree resulting in a substantial thesis. The Department of Computer Science is one of the largest in the UK covering a huge spectrum of Computer Science topics.
CS300 Seminar How many CS300 seminars are we required to participate in? First year CS PhD students are required to attend 2/3 of the seminars. The seminars provide CS faculty with the opportunity to speak for 40 minutes about their research. Allowing new CS PhD students, the chance to learn about the professor's areas of research before permanently aligning. Are the CS300 seminars recorded ...
The PhD in Computer Science is intended for students who already have a good first degree in Computer Science or a related field. For entry to the PhD programme, we require at least a 2:1 undergraduate degree, or a qualification equivalent to a UK Masters degree with a minimum average grade of 60%. We are willing to consider your application if ...
Find out how much time it'll take to get your PhD in computer science and the rewards you can expect to reap after graduating!
A PhD program typically takes four to seven years, but a variety of factors can impact that timeline. A PhD, or doctorate degree, is the highest degree you can earn in certain disciplines, such as psychology, engineering, education, and mathematics. As a result, it often takes longer to earn than it does for a bachelor's or master's degree.
The Computer Science Ph.D. program typically requires two to four years beyond the M.S. degree. Most Computer Science Ph.D. students study at Clemson University in Clemson, SC, but may also study at the Zucker Family Graduate Education Center in Charleston, SC. The program cannot be completed online.
Electives can be selected from the following list in the areas of: Computer Science; Cybersecurity; and Data Science. Core Required Electives (choose nine) Credits: CSCI 606: Distributed Systems: 3: This course introduces the principles and practice underlying the design of distributed systems, both Internet-based and otherwise.
Here is some more information on Ph.D. computer science programs: Requirements. To get accepted into a doctorate computer science program, you must first obtain a bachelor's degree in computer science or another relevant area. Many programs also require you to obtain a master's degree in preparation.
The PhD in Computer Science offers exciting opportunities to do cutting-edge research in an internationally renowned environment. The results of the 2021 REF rank Warwick Computer Science 4th out of 90 UK Computer Science departments. This cements our position as one of the top Computer Science departments in the UK, a position we have held for some time under different assessment methodologies.