The PhD programme lasts four years, including a first year of intensive instruction in techniques and research in theoretical neuroscience and machine learning.

In their first term, all students take the core courses in theoretical neuroscience (TN), systems neuroscience (taught with SWC) and machine learning (ML), after which they generally choose to concentrate on one of these fields. TN and ML continue throughout the second term, while the students start their research projects. Students typically sit exams for TN and ML during the second term.

In their second year, students are expected to continue working on their thesis project. Students also do a 2-month rotation in a field that is not related to their PhD thesis (i.e. if you focus on theoretical neuroscience, you do a rotation on machine learning). At the end of the second year, students write an upgrade report on their progress and any future plans, and give a presentation on this report to the rest of the unit. Having passed all the assessments, students then transfer from MPhil to PhD and are devoted to research for their remaining tenure.

Throughout the training programme, students are immersed in a strong informal educational environment, comprising regular short talks, research reports, journal clubs and ad hoc reading groups; extensive seminar programs in the Unit itself and its neighbours (including ICN , FIL , Psychology at UCL and Birkbeck, Computational Statistics and Machine Learning and Statistical Science ); and attendance and participation in international conferences. Furthermore, the Unit endeavours to function as a single integrated research group, and so students have ready access to all members of the faculty, not just their immediate supervisors.