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The PhD Computer Science programme at IUC supports original research in artificial intelligence, distributed systems, cybersecurity, and software engineering. After doctoral coursework, you will join a research group aligned with your interests, contribute to publications, and defend a dissertation that advances the state of the art. Our faculty maintain active collaborations with European and African universities, offering co-supervision and exchange opportunities. PhD Computer Science is taught as one award, not a list of unrelated modules. The published length is 3–5 years, and the credit total is 60. Students move from Advanced Algorithms & Complexity through Advanced Algorithms & Complexity; Research Methods in Computer Science; Specialist Doctoral Seminar (elective area); Doctoral Research Skills & Ethics; PhD Candidacy Examination; Doctoral Dissertation Research, and finish on Doctoral Dissertation Research. Each course has a question, a method, and a submission. In this field, students specify a small system, show how it was tested, and state how it fails. Reading is a specification, a test note, and an incident or post-mortem. The artefact a marker expects is a specification or reviewed component with tests and a trade-off note. The award is built so that a graduate can do the following in practice: Conduct publishable research in a specialised area of computer science Master advanced mathematical and experimental methods in computing Present research at international conferences and in peer-reviewed journals Teaching assumes the student can read a source, attempt a problem before the seminar, and revise after feedback. Attendance at live seminars is part of the design. The capstone or final course must use the methods of the earlier courses; a project that ignores them does not pass. The pages for each course name the topics that are examined. Those topics are the syllabus. A brochure line is not a substitute for them.
Research groups meet weekly with paper readings and prototype demos. GPU cloud credits support ML dissertations. Co-supervision with partner universities in Europe and Africa is available for comparative systems research.
Faculty spotlight
Professor James Okello leads the Security & Systems lab; Dr. Elena Vasquez directs the Responsible AI research cluster.
Study online
Online tuition is completely free. Study from anywhere in Egypt, the Arab region, and worldwide with full digital flexibility.
| Code | Course | Credits · hours |
|---|---|---|
| PCS701 | Advanced Algorithms & Complexity Advanced Algorithms & Complexity (PCS701) is a 6-credit course on PhD Computer Science, with 60 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Advanced Algorithms & Complexity as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 6 · 60 h |
| PCS702 | Research Methods in Computer Science Research Methods in Computer Science (PCS702) is a 6-credit course on PhD Computer Science, with 60 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Research Methods in Computer Science as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 6 · 60 h |
| PCS703 | Specialist Doctoral Seminar (elective area) Specialist Doctoral Seminar (elective area) (PCS703) is a 6-credit course on PhD Computer Science, with 60 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Specialist Doctoral Seminar (elective area) as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 6 · 60 h |
| PCS704 | Doctoral Research Skills & Ethics Doctoral Research Skills & Ethics (PCS704) is a 6-credit course on PhD Computer Science, with 60 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Doctoral Research Skills & Ethics as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 6 · 60 h |
| Code | Course | Credits · hours |
|---|---|---|
| PCS801 | PhD Candidacy Examination PhD Candidacy Examination (PCS801) is a 0-credit course on PhD Computer Science, with 10 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using PhD Candidacy Examination as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 0 |
| PCS802 | Doctoral Dissertation Research Doctoral Dissertation Research (PCS802) is a 36-credit course on PhD Computer Science, with 360 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Doctoral Dissertation Research as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 36 · 360 h |
Modules are assessed through a published mix of coursework, applied projects, and examinations. Exam windows are announced in advance so students in other time zones are not forced into overnight sittings. Alternative arrangements are available where documented.
The published duration is 3–5 years. Teaching language: English. Actual time-to-complete depends on mode and any recognised prior learning.
You may study this award fully online from your country, or — where published — on campus at IUC. Online study does not require a student visa. Campus study may.
Degree tuition for this award is published as £0 / tuition-free on the online pathway. Examination or administrative fees may apply at checkout — never an annual tuition invoice. Check the Fees page for any extras.
Requirements are grouped on this page (academic, English, documents, research). Equivalent qualifications are considered. English may be waived after prior English-medium study.
Assessment is typically a mix of coursework, projects, and examinations. Doctoral awards include a thesis or dissertation and an oral examination. Details sit in the programme specification and module outlines.
Recognition of the award for local employment, professional licence, or ministry attestation is decided by your employer or regulator. Imperial University in Cairo publishes verification pages for certificates. We do not claim automatic equivalence in every country.
Start an application on this website. Progress is saved from the first step. Admissions: admissions@iucairo.co.uk.
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