The CDT programme provides a comprehensive, state-of-the-art understanding of Autonomous, Intelligent Machines and Systems. This combines theoretical foundations, systems research, academic training and industry-initiated projects, and covers a range of topics aligned to the four Key Skills Areas.
Our programme covers both practical and theoretical aspects. The Departments of Engineering Science and Computer Science have an excellent track record of developing practical systems and evaluating them in real-world applications (e.g. self-driving cars and sensor networks for environmental monitoring).
Taught Course Training
In your first two terms of study, you will take aroud 15 exciting cuttin-edge courses. Each course will typically take 1-2 weeks, consisting of 2-3 hours of lectures each morning, followed by laboratory sessions in the afternoon. These can be interactive modules, project work, individual and team assignments. Each module will emphasise case examples from across the breadth of our Autonomous Systems vision
See the list of CDT Taught Modules that you'll be studying.
In the first year, all students are supervised by both the Director and Co-director who are members of the core academic staff of the CDT. You will meet both of these, as well as the CDT Administrator regularly throughout this period, as a means of assessing progress and discussing academic issues.
In the second half of Year 1, you will be required to take two 8-10-week research projects, one with an industry partner, and the other with a world-leading academic/expert who are members of the CDT academic team in either Engineering or Computer Science, or even jointly supervised. This gives each student experience in undertaking a small research project, one which could seed or turn into a substantive DPhil project.
You will have the chance to choose projects of interest, which normally will be precursors to your DPhil (PhD) study and will help you shape your research topic and further develop your hands-on research skills.
DPhil Research and Supervision
A summary of potential research projects is produced each year by the list of approved supervisors. In addition, you are encouraged to devise projects based on your own research ideas and develop a project in collaboration with potential supervisors. All projects will be vetted by the CDT Management team.
You will select a project and your main research supervisor at the beginning of Year 2. Throughout the research component, primary academic responsibility for each student will reside with their research supervisors, but for each student a member of the core CDT management team will act as a mentor throughout the Programme, offering advice and guidance both academic and pastoral.
Transferable Skills Training
We aim to train students in four critical areas:
- Communication & academic skills, including academic reading, writing and presentation skills
- Business & commercial, including innovation, IP curatorship and entrepreneurship
- Career & development, including training on future employment planning and engagement with the University’s careers services
- Ethics, society & law: We organise an annual mini-course on ethics, in which you will be asked to consider the ethical implications of building autonomous intelligent machines and systems
Student and faculty interactions are continually encouraged in a research seminar series, attended by all CDT students. You will have the chance to meet students from different cohorts, as well as those outside the CDT but researching in the AIMS area.
These research seminars will be used to discuss research papers, and as a vehicle for rehearsing conference talks and building links between different groups.
Internships and industrial placements into Oxford
Industry and commerce also have an active participation in the CDT programme, offering internships in their labs along with placements of industrial partners to work with our students in Oxford.
You will spend 1-2 months over the first or second summer in an industrial lab to gain experience in industry-led projects, expanding your horizons by engaging in an AIMS topic that is related to but not necessarily the same as your thesis. After the end of the internship, we encourage further interaction by inviting your industrial supervisors to join your research group in Oxford for short periods of time.
An opportunity to present the results of your research to other students, industrial partners, and invited researchers from other universities.
As part of this we invite our industrial collaborators to share the latest problems and market trends, and discuss opportunities for future collaboration with our students.
We plan for a two day outreach event in the training programme, during which you will be encouraged to demonstrate the systems built during your group project, individual short research project, or later on as part of your PhD research. You will show them to beneficiaries such as companies and government departments, as well as schools and local communities.
Organisation and Leadership Skills Training
In Year 4, your cohort will be asked to help organise the Annual CDT Workshop, inviting keynote speakers, participating in the program committee, reviewing papers submitted by 2nd and 3rd year students, and publicising the workshop to other universities and industrial partners beyond those directly involved in the CDT.
"The AIMS CDT is a superbly structured PhD program. Its students gain foundational training across a wide range of machine learning topics and, via its first year mini-projects, a smooth transition into the role of doctoral researcher."
- Siddartha Ghoshal, Former Student
Graudates of the AIMS CDT are equipped for leadership roles in industry both nationally and internationally. This is thanks to the positive group dynamic, both within and between year groups, and the increasing responsibility and external exposure adopted by our students throughout their time here.
It is anticipated that other students will continue on and undertake postdoctoral research, probably developing the work in their theses towards product.