Title: SCH31: Developing crime predictive models and evaluating the utility of prediction outputs amongst crime prevention practitioners
Funding: A full Home/EU fee waiver or equivalent fee discount for overseas students (£5,103 in 2020-21) (further fee details - international students will need to pay the balance of their fees) plus a doctoral stipend equivalent to the RCUK Minimum Doctoral Stipend (£15,285 in 2020-21).
Application deadline: Tuesday 31 March 2020
Start date: October 2020
Duration: 3 years (full time)
Location: Colchester Campus
The aim of this cross-disciplinary PhD is to better inform and improve the decision-making capacity of police officers so that we can prevent crime and speed up police interventions.
We will develop machine learning models predicting in which environmental settings crimes are more likely to take place in order to improve the effectiveness of police interventions and the well-being of the population.
The project will span two stages, both involving psychology and data science in a real and in-depth collaboration.
First, the project will involve developing a series of predictive models based on a wide range of crime data held by police as well as environmental factors (e.g. population density, deprivation index, amenities etc.). The predictive models will be based on past data provided by the Essex Police and will help to identify hotspots where crimes are more likely to happen so that resourcing can be allocated more effectively to reduce crime rate and target police interventions.
A series of psychological experiments will then examine the extent to which different predictive models are accurate and can improve staff resource allocation in game-like simulations with human participants.
In a second phase, we will focus on maximising decision quality and measuring and curbing particular cognitive and social biases expected to occur when practitioners rely on algorithms probabilities.
We will focus on the cognitive trend bias (e.g., increasing probabilities are seen as even more certain), the cognitive over-reliance on extreme probabilities (e.g., one can fail to consider a 20% chance of no event when there is an 80% probability of a crime taking place) using the same resource allocation game as before.
We will also consider the social consequence of using the algorithms for specific communities using a stop and search decision task.
The award consists of a full Home/EU fee waiver or equivalent fee discount for overseas students (further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,285 in 2020-21), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.
Lead supervisorDepartment of Psychology, University of Essex
Dr Juanchich is a Senior Lecturer in Psychology. Her research focuses on helping people make better decisions. She is an expert in data communication and behaviour change as well as an open science advocate. For this project, she is interested in testing whether we can transform big-data predictive analytical techniques into meaningful decision-aid for crime prevention practice.
Co-supervisorDepartment of Mathematical Sciences, University of Essex
Dr Dai is a Reader in Statistics at the Department of Mathematical Sciences. He is the Catalyst Project risk-stratification team leader and has been working on spatial statistical modelling for knife-crime data with Essex Police for nearly a year. This PhD scholarship application will further support his work in applied spatial statistics and delivering potential impacts in the future.
You can apply for this postgraduate research opportunity online.
Please include your CV, a cover letter, and transcripts of UG and Masters degrees in your application.
If you are an international applicant who will require a Tier 4 visa please also include a personal statement in your application.
The University has moved to requiring only one reference for PhD applications and these can be received after a conditional offer has been made so the absence of these will not hold up the recruitment process.
When you apply online you will be prompted to fill out several boxes in the form:
If you have any informal queries about this opportunity please email the lead supervisor,Dr Marie Juanchich (firstname.lastname@example.org)
You can find the terms and conditions of this studentship here (PDF).