MRes/PhD project proposal opportunity - UKRI CDT in AI enabled Healthcare

Research laboratory scene

CLOSED: This is match funding therefore there will be two PhD studentships available for AI projects based within the GOSH BRC.

Internal GOSH/ICH and external applicants. 

As many of you are aware as part of our BRC Education Theme we have provided funding for a PhD studentship in UCL’s new CDT in AI enabled healthcare led by Prof. Geraint Rees (https://www.ucl.ac.uk/aihealth-cdt/). This is match funding therefore there will be two PhD studentships available for AI projects based within the GOSH BRC (this is in addition to any others that may be funded through DRIVE). The CDT scheme starts in October this year. Studentships will last for four years therefore in the first instance, projects that are submitted should work initially as an MRes project but should be something that the student could pursue for a PhD if they choose to continue with the project. It must be feasible for students to complete the MRes project and write a 15,000 word thesis in months 6 - 12 of the academic year 2019-20 (i.e. starting Oct-19).

To propose a project supervisors need to meet all of the usual requirements for being a UCL supervisor (https://www.ucl.ac.uk/hr/docs/phd_student_supervision.php), and they should either have a track record of research in AI, or will need to make a case as to why they should be considered an appropriate supervisor of an AI project. 

The project and supervisor nomination forms are attached. Completed forms should be returned to aihealthcdt@ucl.ac.uk by Wednesday 31st July 2019. Please copy in BRC@gosh.nhs.uk when you return these forms if you are proposing a project with a connection to GOSH/ICH that would be eligible for funding through the BRC – this could be any translational project leading to benefits to children with rare or complex diseases including supporting the development of new treatments, biomarkers, diagnostics or imaging techniques. 

CDT in AI-enabled Healthcare Systems - Project Form (37.56 KB) 

CDT in AI-enabled Healthcare Systems - Supervisor Form (39.15 KB)