Student Casual – Research Assistant - Mathematical Modelling of Crime – Social Policy, Sociology and Criminology – Grade 6 – 907725

Please note that this vacancy may be taken down early depending on the number of applications received. We advise you to submit your application promptly.

Our offer to you

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Job context

Most mathematical models of crime look at where and when offences occur. MATCH instead explores how people’s interactions with one another may influence their likelihood of offending. The project has already developed an agent-based model, which the Research Assistant will help extend. The model is described in the preprint Agent-based dynamics of criminal propensity.

Job summary

The Research Assistant will join the interdisciplinary team of Dr Svingen (Criminology) and Dr Luo (Mathematics) to extend the existing agent-based model. The main task is to develop the model so that individuals’ perceptions of their environment can change as they gain experience, and to investigate how this affects the results. This work will form the basis of a second paper, on which the Research Assistant will be a co-author. There may also be opportunities to present the findings at academic conferences with the project team.

Main duties

• Extend the existing agent-based model to reflect how individuals’ perceptions of their environment change over time
• Test the model under different assumptions and analyse how changes in its parameters affect the results
• Produce clear figures and visualisations to communicate the findings
• Contribute to a review of research using mathematical approaches to explain the causes of crime
• Help organise the MATCH workshop, including the call for participation, correspondence with participants and practical arrangements
• Support the MATCH research network by maintaining contact lists and sharing project updates
• Keep clear documentation of code and results, and report progress at regular project meetings
• Contribute to preparing the results for publication

Required knowledge, skills, qualifications & experience

• Essential: currently enrolled as a PhD student at the University of Birmingham
• Essential: experience in mathematical or computational modelling, such as agent-based modelling, opinion dynamics or dynamical systems
• Essential: proficiency in at least one programming language
• Essential: ability to work independently and communicate results clearly to non-specialists
• Essential: an interest in applying mathematical and computational methods to understanding social and behavioural phenomena
• Desirable: experience reviewing academic literature
• Desirable: experience helping to organise academic events
• Desirable: experience either researching or communicating research across disciplinary boundaries

Further details

The working pattern will be up to 7 hours per week, arranged flexibly around the student’s studies (91 hours in total).

For any informal queries, please contact Dr Evelyn Svingen (e.svingen@bham.ac.uk).

The University of Birmingham restricts all students to working up to 20 hours per week during term time for a maximum of 13 consecutive weeks. If your application is successful and your course does not follow the usual academic term timetable (e.g.  PGT, PGR or PhD student), you and your supervisor must formally agree vacation periods if this role exceeds 20 hours per week. In addition to this, please be aware if you are an international student you will be required to apply to the Registry for the appropriate authorised absence.

You are only eligible to apply to this role if you are a current University of Birmingham student. If you are not a University of Birmingham student your application will not be considered.

To work you will need to carry out a right to work check. These checks will need to be completed prior to work commencing.

Regarding the use of AI in applications, we review hundreds of applications and shortlist candidates based on their unique perspective, motivations and potential. Cover letters generated through, or edited by, AI tools (e.g. ChatGPT or CoPilot) are easy to identify. They produce generic answers and will not score highly enough to progress. You may use AI tools for research, but all written content in your application must be your own work. Authenticity and originality are key to standing out in this process.

Due to the high volume of applications we receive, we’re unable to contact all applicants individually. You can check the progress of your application by logging into the Worklink jobs portal using the same email address you used to apply. If you haven’t heard back within six weeks of the closing date, please assume your application has been unsuccessful.