SUPERVISOR COMPETITION FOR ESRC-FUNDED STUDENTSHIPS IN ARTIFICIAL

INTELLIGENCE - DEADLINE 16.00 GMT ON 17 APRIL 2018

 

The ESRC has been allocated 7 additional studentships focussing on Artificial Intelligence, which it will allocate via a supervisor-led competition across the DTPs. The key points and the application process and deadline are summarised below, and are also available here. There are also FAQs, located at the bottom of this page.

Please note the very tight turnaround time for this competition: supervisors are required to submit their applications to the SeNSS office by 16.00 on 17 April 2018.

 

Key points for this competition:

1) Applications must address the priority theme of applications and implications of AI). Further information on this theme can be found in Annex I of the guidance on the UKRI CDT call which is available at:  https://www.epsrc.ac.uk/files/funding/calls/2018/ukriaicdts/

2) Whilst the primary research area must be within the social sciences, the ESRC is encouraging inter/multidisciplinary working both within and beyond the social sciences, as long as at least 50% of the proposed programme of research is within ESRC remit. Please refer to the list of research areas that fall within ESRC remit (www.esrc.ac.uk/funding/guidance-for-applicants/is-my-research-suitable-for-esrc- funding/discipline-classifications) for further information.

3) Whilst it is not mandatory for these studentships to involve business or industry project partners, this is strongly encouraged by the ESRC. If your application is for a collaborative AI studentship, you will need to ensure that a collaboration agreement is in place for the start of the studentship.

4) Please note that these awards are for new studentships; they cannot be used to fund projects already underway.

5) Each DTP can submit up to a maximum of two proposals for consideration by the ESRC.

 

Application process and deadlines:

1) Potential supervisors must complete an ESRC proforma. The criteria for assessing the applications are outlined here (please see page 2). The application must be accompanied by a letter of support from the DTP Director.

2) The internal SeNSS deadline for supervisors to email their applications to the SeNSS office (admin@senss-dtp.ac.uk) will be 16.00 on 17 April 2018. This is to give the core team time to sift these applications to identify the best two applications to submit to the ESRC, and for the acting Director to write the required letter of support for these applications, ahead of the ESRC deadline of 16.00 on Friday 20 April 2018.

3) The applications forwarded to the ESRC will be assessed by a specially convened ESRC panel and, if successful, SeNSS can recruit a student to start in October 2018. 

 

FAQs

Am I eligible to bid for an ESRC-funded AI studentship?

The primary supervisor must be part of one of the 13 SeNSS disciplinary Pathways at one of our 10 partner universities. (For information on our Pathways and partner institutions, please go to the "About" page of this website.) 

Is my research proposal eligible for this bid?

A great deal of excellent work on AI is not related to social science. In order to bid for one of these studentships through SeNSS, the central question under investigation must be a social science one or have direct implications for social science.

Can I bid for a studentship where the second supervisor is not a member of one of the 13 SeNSS disciplinary Pathways?

A joint project with, for example, someone from a computing department seems likely to be the sort of thing that is proposed. In this example, the second supervisor could be based in a computing department (even though none of our pathways is linked to a computing department), as this might be needed to boost the technical support and training for this student.

Can I bid for a 4-year studentship, or only a +3 studentship?

Both types of studentship are available. However, if your bid is for a 1+3, then the Masters degree must be one of our approved Masters. Please note that, currently, none of our Masters include AI-related training (other than possibly via the research dissertation). If you are awarded an AI studentship, the person you select to take up that studentship will either need to come with some AI relevant skills already, or a careful training plan will need to be created to address the specific training needs in this area.