About the role
The researcher would be conducting analytical work, deploying a mix of data science and modelling tools, for two projects: one focused on spatial networks in developing countries, and the other focused on economic networks. Both projects involve other team members and policy partners. The Research Assistant/ Research Fellow would need to be experienced in Python, and with data science methods (, machine learning), network science and spatial methods. The expected outcomes of the role include co-authorship of at least one academic paper focused on mobility in developing cities. This FTE part time, fixed term post available from and is funded for 9 months in the first instance. Must end by 30th June due to funding constraints. Starting salary offered will be £42, per annum, pro rata, inclusive of London Allowance, due to limited amount of funding available. This appointment is subject to UCL Terms and Conditions of Service for Research and Professional Services Staff. Please visit /human-resources/conditions-service-research-teaching-and-professional- services-staff for more information. We will consider applications to work on a part-time, flexible and job share basis wherever possible. Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Research Assistant Grade 6B (salary - £ 37, - £ 39, including London Allowance per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis. For any queries about the role please contact Neave O'Clery (). A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the ‘Apply Now’ button below.
About you
The postholder will have completed or be currently undertaking a PhD (or have equivalent experience) in a related discipline (spatial data science, quantitative geography, applied maths, economics, statistics, computer science or similar). They will be highly proficient and experienced in coding (using Python or similar) and have extensive experience handling and analysing large complex data sets, including spatial data ( shapefiles and data layers from Google Earth Engine); deep knowledge of applying spatial data science methods and machine learning algorithms in a research context; deep knowledge of network science techniques, , dynamics on networks and community detection. They will also have ability to communicate and collaborate with a variety of non-academic project partners who are actively involved in the projects; ability to write about technical subjects for a non-technical audience; excellent organisational skills and ability to problem solve. For full list of essential and desirable criteria, please see a job description and person specification at the bottom of this page.
What we offer
As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below: - 41 Days holiday (27 days annual leave 8 bank holiday and 6 closure days); - Additional 5 days’ annual leave purchase scheme; - Defined benefit career average revalued earnings pension scheme (CARE); - Cycle to work scheme and season ticket loan; - Immigration loan Relocation scheme for certain posts; - On-Site nursery; - Onsite gym; - Enhanced maternity, paternity and adoption pay; - Employee assistance programme: Staff Support Service; - Discounted medical insurance.
