University of Birmingham

Research fellow - School of Psychology - 105747 - Grade 7

University of Birmingham  •  £37k - £49k/yr  •  United Kingdom of Great Britain and Northern Ireland (Hybrid)  •  2 hours ago
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Job Description

Position Details

School of Psychology

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £36,636 to £46,049 with potential progression once in post to £48,822

Grade: 7

Full Time, Fixed Term contract up to March 2027

Closing date: 14th June 2026

Background

This post will be funded by a multi-million pound award from Wellcome Leap programme awarded to the University of Birmingham to study Untangling Addiction. Our project, entitled “Predicting persistent opioid usage after surgery: Integrating multi-omics, neurobiology, and AI-interviews.”

Our research programme aims to address persistent opioid usage by identifying molecular, neurobiological and cognitive signatures characterizing patients at risk of prolonged opioid use post-surgery.

This post supports the Wellcome Leap funded study ACORN which focuses on the development and validation of persistent pain and opioid usage in patients after major surgery

The post holder will be based within the School of Psychology and Department of Cancer and Genomic Sciences (CGS) and will join the Centre for Health Data Science, working under the supervision of Dr Andreas Karwath and Professor Ali Mazaheri and in close collaboration with the co-investigators, Professor Helen McGettrick and Professsor Fang Gao Smith The post will focus primarily on computational analysis, data transformation, and equity evaluation within a trusted research environment.

The ACORN Team is seeking an individual with a degree or equivalent in Health Data Science, Computer Science, Artificial Intelligence, or a closely related discipline relevant to clinical predictive modelling and fairness in machine learning, who has practical experience in its application using established tools (for example, NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow) and procedures. Experience working with electronic health records or primary care data, and in preparing, structuring, and analysing large-scale longitudinal datasets, is desirable.

Candidates may be asked to prepare a short presentation outlining their suitability for the role. The anticipated start date is July 2026. The post will be offered on a hybrid working basis, with an expectation of at least three days per week in the office.

Main Duties

The responsibilities may include some but not all of the responsibilities outlined below.

  • Developing novel computer-based models, techniques and methods
  • Develop research objectives and proposals for own or joint research, with assistance of a mentor if required
  • Contribute to writing bids for research funding
  • Analyse and interpret data
  • Apply knowledge in a way which develops new intellectual understanding
  • Disseminate research findings for publication, research seminars etc
  • Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline
  • Undertake management/administration arising from research
  • Contribute to Departmental/School research-related activities and research-related administration
  • Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader
  • Collect research data; this may be through a variety of research methods, such as scientific experimentation, literature reviews, and research interviews
  • Present research outputs, including drafting academic publications or parts thereof, for example at seminars and as posters
  • Provide guidance, as required, to support staff and any students who may be assisting with the research
  • Deal with problems that may affect the achievement of research objectives and deadlines
  • Promotes equality and values diversity acting as a role model and fostering an inclusive working culture.

Person Specification

  • A PhD (or near to completion) in the areas of Health Data Science, Computer Science, Artificial Intelligence, or a closely related discipline relevant to clinical predictive modelling and fairness in machine learning,
  • Demonstrable knowledge of statistics and machine leadning
  • High level analytical capability
  • Ability to disseminate research findings through publication and/or oral presentations.
  • Ability to communicate effectively with colleagues from different academic disciplines and deliver information clearly.
  • Self-directed, flexible approach to work.
  • Contribute to the planning and organising of the research programme and/or specific research project
  • Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day-to-day activity in own area that those with protected characteristics are treated equally and fairly

Informal enquiries to Ali Mazaheri, email: a.mazaheri@bham.ac.uk

Use of AI in applications: We want to understand your genuine interest in the role and for the written elements of your application to accurately reflect your own communication style. Applications that rely too heavily on AI tools can appear generic and lack the detail we need to assess your skills and experience. Such applications will unlikely be progressed to interview.

We believe there is no such thing as a 'typical' member of University of Birmingham staff and that diversity in its many forms is a strength that underpins the exchange of ideas, innovation and debate at the heart of University life. We are committed to proactively addressing the barriers experienced by some groups in our community and are proud to hold Athena SWAN, Race Equality Charter and Disability Confident accreditations. We have an Equality Diversity and Inclusion Centre that focuses on continuously improving the University as a fair and inclusive place to work where everyone has the opportunity to succeed. We are also committed to sustainability, which is a key part of our strategy. You can find out more about our work to create a fairer university for everyoneon our website

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