Research Assistant/Research Fellow (Part Time)

About us

The Bartlett Centre for Advanced Spatial Analysis (CASA) is globally recognised as a leading academic department, researching and teaching the science of cities. A truly interdisciplinary centre, with staff hailing from backgrounds in subjects as diverse as Geography, Transport Studies, Mathematics, Physics, Computer Science, Statistics, Planning, Architecture, the Humanities and the Social Sciences, for more than 20 years we have been combining theory with novel data, sensors, computational models, analysis and cutting edge visualisation to generate new knowledge and insights addressing problems with a spatial dimension and an urban and regional focus.

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 (e.g., 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 0.6 FTE part time, fixed term post available from 01.10.2024 and is funded for 9 months in the first instance. Must end by 30th June 2025 due to funding constraints. Starting salary offered will be £42,099 per annum, pro rata, inclusive of London Allowance, due to limited amount of funding available.

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 (e.g. 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, e.g., 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.

What we offer

As well as the exciting opportunities this role presents, we also offer some great benefits.

Our commitment to Equality, Diversity and Inclusion

As London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL’s workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.

Job ref.: B04-05355

Closing date: 16-09-2024 - 23.59 (UK time)

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