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UKRI AI CDT PhD in Decision Making for Complex Systems, Cambridge/Manchester (United Kingdom)

open Verified SCH-DB-221 · 02 Computer Science & AI · United Kingdom

A UKRI AI Centre for Doctoral Training PhD in decision making for complex systems, split between one year at Manchester and three years at Cambridge's Department of Computer Science and Technology. Successful applicants receive full UKRI funding for fees and maintenance, with a 13 May 2027 application deadline and a 1 October 2027 start.

Amount / fundingFull UKRI funding (fees and maintenance) covering one year at Manchester and three years at Cambridge. Most awards are made to applicants who qualify for Home fees, but a number of awards are available for international applicants. The exact stipend rate is not stated in the rendered page text — check official page.
DeadlineApplication deadline 13 May 2027; applications opened 9 September 2026; course starts 1 October 2027 (official Cambridge postgraduate course page).
Start date1 October 2027
LevelPhD
Funding typefull
Field02 Computer Science & AI

About this scholarship

A UKRI AI Centre for Doctoral Training PhD in decision making for complex systems, split between one year at Manchester and three years at Cambridge's Department of Computer Science and Technology. Successful applicants receive full UKRI funding for fees and maintenance, with a 13 May 2027 application deadline and a 1 October 2027 start.

Minimum requirements

Applicant to the UKRI AI CDT PhD in Decision Making for Complex Systems (Department of Computer Science and Technology, University of Cambridge), 3-4 years full-time or 4-7 years part-time. Both UK and overseas candidates are encouraged to apply (official page). Exact academic entry requirements were not visible in the page render (JavaScript required) — check official page.

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Always verify deadline, amount and eligibility on the official page before applying. Values marked ESTIMATE are based on a previous cycle and are not confirmed for the current round.

Tags: artificial intelligence, decision making, complex systems, machine learning