ESRC IAA RESEARCH ASSOCIATE
Manchester, United Kingdom
30 Oct 2026
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Overview
- Institution
- The University of Manchester
- Location
- Manchester, United Kingdom
- Field
- Computer Science
- Deadline
- 30 October 2026
- Hours
- 35 per week
About this position
Job Description
This is an exciting opportunity for an ambitious graduate with the ability and confidence to work on a research project for developing eXplainable AI-powered Decision Models (XAI-DMs) for Insurance Under-writing, which is funded by ESRC IAA to The University of Manchester (UoM) together with Protector In-surance as industrial partner.
The University of Manchester is looking to recruit a decision scientist, artificial intelligence (AI) modeller, system scientist to undertake this project, which is based on the research conducted by UoM experts over many years in areas of decision science, systems science, AI and Data Science to develop the Evidential Reasoning (ER) theory, including the Maximum Likelihood Evidential Reasoning (MAKER) framework for probabilistic reasoning with imperfect data, the ER rule for combination of uncertain evidence acquired from imperfect data and human judgment, the ER approach for multiple criteria decision making under uncertainty, and the Belief Rule Base (BRB) methodology for probabilistic system modelling and intrinsi-cally explainable machine learning funded by many EPSRC grants.
The RA position will provide the successful candidate with a unique opportunity to take the lead on a strategic project, aimed at translating the ER theory and industrial domain knowledge to develop new XAI-DMs for Insurance Underwriting and to integrate them into existing working practices for Protector Insur-ance, which will be supported by the specialists of the company. The RA will therefore be faced with the challenge of understanding both the theory and the practical applications of decision modelling, data an-alytics, probabilistic inference, XAI decision modelling and evidence-based decision making to support the development of the XAI-DMs; and translating the technical know-how into a form that can be easily un-derstood and used by users within Protector Insurance.
Candidates will require a minimum 2:1 with doctoral research experience in Systems Science, Decision Science, Operational Research, Data Analytics, Artificial Intelligence, or Applied Statistics with Decision, or a PhD degree in the-afore mentioned or related subject areas, with evidence of a strong grounding in probabilistic data analysis and reasoning, XAI decision modelling, decision analysis, multiple criteria assessment, and software development in Python or equivalent.
This post is funded through an ESRC IAA award together with Protector Insurance, a UK Government scheme intended to promote sustained and mutually beneficial relationships between universities and industry.
Based at Alliance Manchester Business School and Protector Insurance, the successful candidate will work directly with the supervisors from the University and with other researchers and practitioners from Pro-tector Insurance.
(Grades 6-9)
Our benefits include
- Generous employer contribution pension
- 29 days annual leave plus bank holidays, along with Christmas closure
- Ride to work and EV car scheme available
For more information, please see University of Manchester Benefits . You can also find information on our Flexible and Hybrid working here .
We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy .
Enquiries about the role, shortlisting and interviews
Prof Jian-Bo Yang; Email: jian-bo.yang@manchester.ac.uk Tel: 0161 3063427
Prof Dong-Ling Xu; Email: ling.xu@manchester.ac.uk Tel: 0161 2750941
General enquiries and administrative support
recruitmentservices.people@manchester.ac.uk
Technical and job portal support
https://jobseekersupport.jobtrain.co.uk/support/home
Applications close at midnight on the closing date.
Further particulars (with person specification) linked below.
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