Research Fellow

We are seeking an enthusiastic and innovative Research Fellow to join the Centre for Environmental Research and Justice (CERJ) and the Centre for Health Data Science at the Medical School University of Birmingham. You will be working in a vibrant, interdisciplinary research ecosystem, driving cutting-edge research at the intersection of human health and health data science. This exciting role offers the opportunity to contribute to major EU-funded research programmes, including PARC (Partnership for the Assessment of Risks from Chemicals).

The successful applicant will contribute to several clinical and biomedical projects and will apply and develop novel machine learning and statistical models that allow for prognosticating disease evolution, treatment outcome, and resistance. The post holder will analyse data from a variety of clinical and medical data sources including structured and unstructured and/or sequential data, like images, text, and time series. An excellent network of biomedical and technological collaborations, as well as opportunities for discovery validation and translation into clinic or pharma by domain experts. The successful candidate will actively promote FAIR data practices and will have opportunities to contribute to teaching, training, and wider community engagement.

The duration for the post will be 2 years offering a considerable scope for innovation and academic development.

Role Summary:

- Develop agentic AI systems to coordinate workflows and computational tools according to different clinical needs, patient presentations, and care pathways.
- Deploy and operate large models (LLMs/VLMs) and other foundation models in local or on-premises computing environments to support data security and patient confidentiality.
- Develop knowledge bases that capture clinical guidelines and domain knowledge to extend the capabilities of general-purpose large models for clinical applications.
- Develop retrieval-augmented generation (RAG) pipelines and agentic AI systems for clinical knowledge retrieval, reasoning, and decision support.
- Develop and evaluate cutting-edge AI approaches (e.g., multimodal and multi-agent techniques) for medical applications.
- Curate, integrate, preprocess, and analyse biological and medical data sets from a variety of modalities and data origins and apply cutting-edge semantic technologies for their integration.
- Manipulate, integrate, and analyse small and large clinical and biomedical databases.
- Communicate research results through conference presentations, scientific publications, or project reports.
- Analyse and interpret research findings and results.
- Contribute to generating funding.
- Work within specified research grants and projects and contribute to writing bids.
- Operate within area of specialism.
- Contribute to licensing or spin-out deals with demonstrated commercial success and/or public understanding of the discipline.

Main Duties:

- Contribute to developing new models, techniques and methods.
- Collect research data 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.
- Develop and apply advanced AI techniques to address research questions in medical and clinical applications.
- Contribute to identifying and shaping new research directions in agentic AI, foundation models, and related areas of medical AI.
- Analyse and interpret a variety of medical data.
- Develop research objectives and proposals for own or joint research, with assistance of a mentor if required.
- Contribute to writing bids for research funding.
- 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.
- 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.
- Foster a fair and equitable workplace for all staff.
- Identify and respond to equality and diversity issues in line with relevant university policies and procedures.

Person Specification:

- PhD (or near completion) in Computer Science or a field relevant to medical AI.
- Fluency in relevant models, techniques or methods and ability to contribute to developing new ones.
- Ability to coordinate own work with others to avoid conflict or duplication of effort.
- Ability to develop agentic AI systems for medical or clinical applications.
- Ability to deploy large models (LLMs/VLMs) in local or on-premises computing environments.
- Ability to curate, integrate, preprocess, and analyse clinical data from different modalities (e.g., electronic health records, physiological signals, and imaging).
- Ability to build and maintain clinical knowledge bases to extend the capabilities of general-purpose large models for clinical applications.
- Ability to develop retrieval-augmented generation (RAG) systems for clinical and agentic AI applications.
- Ability to demonstrate an understanding of both science and informatics.
- Ability to innovate and develop ideas into grant proposals.
- Ability to write concise and timely scientific papers and reports.
- Ability to plan and prioritise work effectively to meet deadlines.
- Experience in medical AI, including agentic AI, multi-agent systems, and multimodal modelling and analysis.
- Proven and extensive experience with semantic technologies, Data Science, Semantic Web with emphasis on ontology engineering and Machine Learning.
- Proficiency in high-level (e.g. Python, C++, Java) and low-level (C) programming languages, database design and handling, and knowledge of commonly employed libraries such as SciKit-Learn, Pandas, Keras, TensorFlow, or similar.
- Proven ability to work collaboratively within multidisciplinary and/or national and international teams.
- Capable of working independently and proactively, including time management.
- High-level analytical capability.
- Ability to communicate complex information clearly, including the ability to clearly present complex technical data to a range of audiences.
- Ability to assess resource requirements and use resources effectively.
- Understanding of and ability to contribute to broader management/administration processes.
- Knowledge of the protected characteristics and duties under the Equality Act 2010, including fostering good relations and advancing the university's Public Sector Equality Duty (PSED).