Research Fellow in Inclusive Green Infrastructures Ref 2813

School/department: School of School of Engineering and Informatics
Hours: 0.35 FTE
Contract: Fixed term for 21 months with the possibility of extension
Reference: 2813
SalaryGrade 7, starting at £33,797 and rising to £40,322 per annum pro rata
Placed on: 22 November 2019
Closing date: 10 December 2019. Applications must be received by midnight of the closing date.
Expected interview date: 18 December 2019
Expected start date: January 2020


Job description

The Data Science group is seeking a Research Fellow to assist with a British Academy project “Inclusive Green Infrastructure for Urban Well-Being”. The successful candidate will be based at the Department of Informatics at the University of Sussex School of Engineering and Informatics, and will become a member of the Predictive Analytics (PAL) Lab. In addition to undertaking high quality research and publishing in top machine learning and computer vision conferences/journals including NeurIPS, ICML, CVPR, and TPAMI, the PAL group also creates significant impact by providing support, technology, and highly-trained specialists to a new generation of technology companies/charity foundations.

The goal of the project is to develop a novel transdisciplinary methodology for city-region land-use mapping and analysing how land-use change impacts green infrastructures, environmental services, and well-being. This is a new project including collaborators from the Science Policy Research Unit (SPRU), University of Sussex, Centre of Social Medicine and Community Health, Jawaharlal Nehru University, and School of Publication Administration, Zhongnan University of Economics and Law.

Applicants must have a Bachelor’s or Master’s degree in computer science, statistics, physics, mathematics (or related disciplines), and experience with the Ruby on Rails and Stimulus web development frameworks. Experience with Javascript mapping libraries such as Leaflet or OpenLayers, as well as frontend UI/UX development with libraries such as Bootstrap is a distinct advantage. Informal enquiries are welcome and can be made to Novi Quadrianto, Reader in Machine Learning (N.Quadrianto@sussex.ac.uk), or Fiona Marshall, Professor of Environment & Development (F.Marshall@sussex.ac.uk).

Download job description and person specification Ref 2813 [PDF 159.01KB]


How to apply

Download our academic post application form [DOC 301.50KB] and personal details and equal opportunities form [DOC 162.50KB] and fill in all sections.

Email your completed application, and personal details and equal opportunities form, to enginfrecruitment@sussex.ac.uk.  

You should attach your application form and all documents to the email (don't use a web-based upload/weblink service) and use the format job reference number / job title / your name in the subject line.

You can also send your application by post to Human Resources Division, Sussex House, University of Sussex, Falmer, Brighton, BN1 9RH.

Download our terms and conditions summary for Research Faculty Terms and Conditions [DOC 36.00KB]


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