ESRC-Turing Scholarship

Call for ESRC-funded Alan Turing and Midlands Graduate School Doctoral Studentship at the University of Birmingham

The Alan Turing Institute and the Midlands Graduate School DTP are seeking to recruit one doctoral student to work on an Economic and Social Research Council (ESRC) funded PhD project in the priority area of smart cities. Studying at the Turing offers students a unique opportunity to undertake a data science- focused PhD in a multidisciplinary environment, where experts from different research disciplines work side-by-side to solve problems, generate ideas and transform research into real-world impact.

The student will be supervised by ESRC and Turing fellow, Professor Ganna Pogrebna, who has been granted an ESRC award to drive the development and application of data science for smart cities. Professor Pogrebna will act as the primary supervisor, helping in particular to develop the quantitative and data science skills of the student.

Students will spend a majority of the programme at the Alan Turing Institute in its headquarters at the British Library in the heart of London’s vibrant Knowledge Quarter. Students will be registered at the Department of Economics, Birmingham Business School (University of Birmingham) and will have the additional opportunity to complete the training and development requirements of their University programme. To find out more about what a Turing Doctoral Studentship offers please see full details on the website.

The application could be made for either 1+3.5 programme (Option A) or +3.5 programme (Option B).

Option A:

This option is suitable for students who do not yet have an MA/MSc in Social Research. These students will have to first complete an MA in Social Research at the University of Birmingham (the costs of the programme will be fully covered by the studentship) and then proceed to PhD.

Option B:

Option B is suitable for students who do have an MA/MSc in Social Research, either from Birmingham or another institution. In order to be eligible for Option B, you need to demonstrate that you have completed modules in all of the four ESRC core areas:

  • Philosophy of Social Science Research
  • Research Design, Practice and Ethics
  • Qualitative Research Methods
  • Quantitative Research Methods

Please, note that candidates who do not have MA/MSc in Social Research with the 4 abovementioned modules should apply for Option A.

Conditions

Option A: Students who are required to undertake the Masters in Social Research at the University of Birmingham in 2019-2020 will be provided with an extra year’s funding for their study programme at a Home Fee rate prior to commencing the PhD plus a stipend at the standard UKRI rate: £14,777 (tax free) for 2019-2020. Note that in 2019-2020 the student will be primarily based at the University of Birmingham. In the subsequent 3.5 years the student should plan to spend the bulk of his/her time in London at the Alan Turing Institute. Starting from 2020 the studentship will cover costs of the PhD study programme at a Home Fee rate (equivalent to the home fee at the University of Birmingham) plus the stipend. The stipend will be £20,500 (tax free) per year (subject to annual increases) for 3.5 years. The student will be reimbursed by Turing for travel and subsistence to conferences and meetings up to the value of £2,000 pa. The student will be able to claim a fixed allowance for travel and accommodation from the Alan Turing Institute in relation to visiting their home University.

Option B: The studentship will cover costs of the study programme at a Home Fee rate (equivalent to the home fee at the University of Birmingham) plus the stipend. The stipend will be £20,500 (tax free) per annum (subject to annual increases) for 3.5 years. The student will be reimbursed by Turing for travel and subsistence to conferences and meetings up to the value of £2,000 pa. The student will be able to claim a fixed allowance for travel and accommodation from the Alan Turing Institute in relation to visiting their home University for research purposes.

Criteria

  • First or upper second class level honours degree or master’s degree from a UK academic research organisation
  • Two satisfactory academic or relevant work placement/employment references
  • Students in receipt of a studentship offer will need to provide acceptable proof of legal right to study in the UK and satisfy the current requirements of UK Visa and Immigration, and satisfactorily pass the Institute’s security screening process
  • Degree qualifications gained from outside the UK, or a combination of qualifications and/or experience that is equivalent to a relevant UK degree, may be accepted.
  • Note that only Home/EU students who have been ordinarily resident in the UK for three years prior to the start of the grant ( or individuals who have indefinite leave to remain in the UK and also meet the residency requirements) are eligible to apply

Residential conditions

To be eligible for a full award (stipend and fees), you must have settled status in the UK, meaning there are no restrictions on how long you can stay, and have been ‘ordinarily resident’ in the UK for three years prior to the start of the studentship grant. This means you must have been normally residing in the UK, apart from temporary or occasional absences.

You must not have been residing in the UK wholly or mainly for the purpose of full-time education. (This does not apply to UK and EU nationals.)

EU citizens who do not meet the residency requirements for a full award can apply for a fees-only award. To be eligible, you must be ordinarily resident in an EU member state in the same way that a UK student must be ordinarily resident in the UK.

Project description

The student will work on a project Behavioural Modelling of Space and Time in the City Context: Implications for Urban Wellbeing

Summary of research: Current research in economics and psychology shows that people of different ages perceive time and space differently. This project will systematically measure those differences and relate them to urban wellbeing. The student will use data inference and machine learning algorithms to develop ways in which end users (citizens, households, policy-makers, and businesses) can change their behaviour in order to reach higher levels of urban wellbeing in the city context. (S)he will then design and conduct laboratory and field experiment to test how wellbeing data and behavioural insights should be presented to citizens in order to ‘nudge’ them to make more optimal decisions and to increase urban wellbeing. The responsibilities of the role are to focus on the design and development of: (i) feedback protocols and (ii) incentive mechanisms, informed by the work of the project team on human-computer and human-data interactions; and (iii) evaluation of mechanisms for specifying happiness requirements as well as determining the data flow between the platforms used by the team, partners (SunBath and Databox), and external applications.

The student should have strong quantitative skills and interest in developing of career in behavioural analytics and/or computer science (preferably both). (S)he should have a desire to work across disciplines. The ideal candidate will have some experience in data analytics, inference, and sensing, plus experience in one or more of the following areas: conducting studies with human subjects, coding experience, data mining experience, social media, mobile sensing, and/or applied machine learning, etc.). The candidate should have completed her/his Master of Research in Social Sciences degree before taking up the post.

The student will be supervised by Professor Ganna Pogrebna (University of Birmingham and the Alan Turing Institute). The student will develop an independent programme of research and explore how individual citizens and households could be ‘nudged’ to make better decisions about their urban environment and lifestyle, in order to increase their wellbeing. Even though the project topic is independent, it fits well with the agenda of the proposed fellowship because it will provide insights into how citizens can optimise their behaviour to increase their wellbeing.

Timeline

Application deadline: 7 February, 2019 at 12 noon (GMT). In your cover letter, please indicate whether you are interested to apply for Option A or Option B.

Remote interview: Professor Pogrebna will organise a call or video conference to interview candidates if they are interested in their application between 8-12 February, 2019.

Interview days: 26 February and 27 February, 2019. You will be required to attend for one day but should keep both of them free until your interview time is confirmed.

How to apply

To apply, send the following documents to gpogrebna@turing.ac.uk:

  • Cover Letter (In your cover letter, briefly explain why you are interested in this position).
  • CV (At the end of your CV indicate names and email addresses of 2 referees who could be contacted for references in case you are invited to the interview at the end of February).
  • Transcripts (Please, merge all your transcripts into one PDF file).
  • Filled out Application Form downloadable from here: DOWNLOAD FORM

For any enquiries regarding this position, please contact gpogrebna@turing.ac.uk.