Research Assistant/Research Fellow in Computational Social Science

UCL Eastman Dental Institute
London
1 year ago
Applications closed

Related Jobs

View all jobs

Research Fellow in Data Science

Data scientist (IT) level 6 apprentice - Immunocore Immunocore

Research Assistant/Associate in Cardiac Computational Modelling via Machine Learning and Biomechanics Simulations

Postdoctoral Research Assistant in Health Data Sciences

Postdoctoral Research Assistant in optical neural networks (experiment)

Research Associate – Artificial Intelligence in Cardiac MRI

About the role

We are seeking a motivated and skilled Computational Social Scientist to join our interdisciplinary team as a Research Assistant (without PhD) or Research Fellow (with PhD) focused on the phenomena of small homes in English cities. The postholder will be responsible for developing and delivering a national database of properties in England using EPCs as a source of floorspace data, linking this with Price Paid Data, Zoopla, local planning, and such other housing data as may be identified through record matching protocols incorporating machine learning and Natural Language Processing (NLP). This work will form the basis for time series and spatial analysis of residential property size at multiple scales since . We have completed ‘proof-of-concept’ data linkage work in London but now seek to extend the breadth of our pilot, exploring the wider geographies of very small homes in English cities whilst increasing depth of understanding by assessing whether small homes ever constitute adequate homes. The role is part of the UKRI-funded “No Place Like Home?” project (ESRC/Z/1). The post-holder will interact actively with members of the wider research group, identifying synergies that will help build our collective intelligence about the issue of small housing. Team includes Profs Phil Hubbard and Katherine Brickell, both in the Department of Geography, King’s College London, Prof Helen Carr (Southampton) and Dr Eleanor Wilkinson (Sheffield) alongside Prof Jon Reades (UCL). Further detail about the duties and responsibilities can be found in the job description at the bottom of this page, but these broadly cover: data linkage and exploration, decision-support, collaboration and stakeholder engagement, research and publication, and basic project management to a timeframe.The funding for this role is fixed and affects the duration of the post. The minimum term is 15 months, in the first instance, at Grade 7 with the possibility for extension depending on salary level ( appointment at a lower level would increase the minimum contract length). This can be discussed in greater detail at the interview stage.Starting salary (at Grade 7, Research Fellow) offered will be in the range of £43, - £45, per annum inclusive of London Allowance, due to limited amount of funding available.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 - £38,–£41, including London Allowance per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.This appointment is subject to UCL Terms and Conditions of Service for Research and Professional Services Staff. Please visit for more information. We will consider applications to work on a part-time, flexible and job share basis wherever possible. For any queries about the role please contactProfessor Jon Reades (). 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

You will have a relevant background, such as a degree and/or professional experience, to allow you to engage with both the computational and domain components of the research project. Appointment at Grade 7 requires a completed PhD in a relevant discipline. All other appointments would be at Grade 6. Relevant disciplines include Computational Social Science, Spatial or Geographic Data Science, and Urban Analytics. Relevant professional experience would include work ‘at scale’ in the housing or urban analytics sector. As part of the application and interview process we will be seeking to assess your experience of working with large geospatial data sets and on data linkage problems, your capacity to learn and apply your coding skills to real-world problems, and your knowledge (if any) of the UK planning and housing context. It is essential that you are proficient in at least one of the Python or R programming languages (the proof-of-concept work is in Python), as is a working knowledge of SQL. A basic understanding of Named-Entity Recognition and Natural Language Processing would be highly desirable. However, the ability to work across disciplinary and methodological boundaries is also integral to the project: you will be supporting qualitative and survey work packages through the identification of areas for intensive investigation as well as collaboration around research outputs. The post-holder will have opportunities to work with stakeholders in the public, private, and governmental sectors, so an interest in the communication of research methods and findings to non-technical audiences is desirable. 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.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.