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Lecturer in Large Language Models (LLMs) for Healthcare

King's College London - Biostatistics & Health Informatics

Location: London
Salary: £53,149 to £62,422 per annum inclusive of London Weighting Allowance.
Hours: Full Time
Contract Type: Permanent
Placed On: 22nd January 2025
Closes: 19th February 2025
Job Ref: 105065
 

About Us

King’s College London is an internationally renowned university delivering exceptional education and world-leading research. The university is dedicated to driving positive and sustainable change in society and realising our vision of making the world a better place. The Strategic Vision 2029 looks forward to King’s College London’s 200th anniversary in 2029 and sets out ambitious plans in five key areas:

  • Educating the next generation of change-makers 
  • Challenging ideas and driving change through research 
  • Giving back to society through meaningful service 
  • Working with our local communities in London 
  • Fostering global citizens with an international perspective

The Institute of Psychiatry, Psychology & Neuroscience (IoPPN) is a Faculty of King's College London and the largest academic community in Europe devoted to the study and prevention of mental illness and brain disease. The School of Mental Health & Psychological Sciences (MHaPS) is one of three schools under the IoPPN, comprised of the four departments of Psychology; Social, Genetic & Developmental Psychiatry; Health Service & Population Research; and Biostatistics & Health Informatics. With over 100 Principal Investigators, our research spans development from childhood to old age, encompassing basic research through to the development and implementation of treatments, services and policy. 

King’s College London, through rich collaborations with NHS and industry partners such as Amazon, Databricks and CogStack, and national infrastructure including the NIHR and Health Data Research UK (HDR UK: https://www.hdruk.ac.uk), is at the forefront of clinical Large Language Model Development and Applications and health data science research in the UK. We pride ourselves on the impact of our research, which has led to the deployment of novel informatics applications and platforms to King’s Health Partners (KHP; https://www.kingshealthpartners.org/) and other NHS sites across London and the UK, and beyond. These applications are beginning to realise the potential of large-scale analytics and the promise of data driven healthcare.

About The Role

We are offering an exciting opportunity for Lecturer in Large Language Models (LLMs) for Healthcare in the Department of Biostatistics and Health Informatics at the Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London. The focus of this role is on developing a portfolio of health-related LLMs research which sits within, and benefits from, leading programmes of clinical, health, clinical and bioinformatics at King’s College London. The post holder will work on a range of machine & deep learning techniques and will also be expected to support new submissions to funders as a co-applicant. They will be expected to teach on our undergraduate and postgraduate programmes. This is a full-time post (100% full time equivalent), and will be offered on an indefinite contract.

About You

To be successful in this role, we are looking for candidates to have the following skills and experience: 

Essential criteria

  • PhD in Computer Science, AI, Data Science, or related field 
  • Research portfolio in the use of big biomedical data for better patient care 
  • Knowledge/skills in Health/Clinical informatics & multi disciplinary research 
  • Experience of delivering teaching to postgraduate and/or undergraduate students 
  • Publication record appropriate to career length & level of appointment 
  • Strong publication record in top-tier AI or health informatics journals 
  • Experience in teaching AI, ML, or health informatics 8. Expertise/Interest in large language models (LLMs), GenAI and natural language processing 

Desirable criteria

  • Participation in grant applications to funders 
  • Postdoctoral research experience 
  • Experience in leading AI/health-related research projects 
  • Development of innovative teaching methods 
  • Experience with health informatics standards (e.g., HL7, FHIR)
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