Inkfish Research Scientist (Medical) in Large Language Models

UAG; London; On-site; GBP 44,000 - 52,000; Full time

Job summary

A leading company is seeking a Research Scientist (Medical) to develop innovative Large Language Models for health coaching. The role entails collaborating with AI researchers and ensuring the medical validity of recommendations while working on a groundbreaking international study backed by substantial funding. Candidates should possess a medical degree and experience in public and digital health research.

Qualifications

• Medical degree and Master of Public Health required.
• Experience with LLMs in healthcare contexts.
• Evidence of writing peer-reviewed papers.

Responsibilities

• Develop personalised LLMs for health coaching.
• Evaluate multilingual and culturally sensitive deployments.
• Collaborate with AI researchers to ensure medical validity.

Skills

Medical degree

Experience in AI/LLMs in healthcare

Digital health research

Medical or healthcare-related research

Natural language processing techniques

Project management skills

Education

Undergraduate medical degree

Master of Public Health

Job description

Please note that although this role is advertised as Research Scientist, your contractual job title will be “Research Associate - (Medical) in Large Language Models”

About the role

We are looking for a Research Scientist (Medical) to join our team delivering the EMBRACE study, an innovative research project led by Professor Josip Car. EMBRACE is a visionary, multicomponent international research programme. The first of its kind in the world, supported by Inkfish with £35M core funds over six years. It is a global study of 60,000 participants, including 20,000 mothers, 20,000 infants and up to 20,000 partners. It brings together world-leading clinician scientists across six distinguished healthcare organisations, exceptional AI and technology companies, together with premier biotech companies, with the overarching aim to fast-track major scientific breakthroughs, revolutionise maternal and early childhood health through precision-personalised interventions, powered by a groundbreaking symbiosis of cutting-edge AI combined with human support.

The successful candidate will partake in the development of personalised, context-sensitive Large Language Models (LLMs) for health coaching. By delivering real-time, adaptive recommendations following exercise sessions and integrating multi-modal health and lifestyle data, the post-holder will play a key role in ensuring the medical validity and real-world relevance of the coaching recommendations. Collaborating closely with AI researchers, the individual will integrate medical knowledge into the LLMs, enhance their social intelligence (empathy, theory-of-mind), and evaluate multilingual and culturally sensitive deployments.

We are looking for an individual with a medical degree, a strong track record in public health and digital health research including peer-reviewed publications, an interest in LLMs as well as experience of using LLMs for healthcare research.

The post is based in the Faculty of Life Sciences and Medicine, and will be closely affiliated with the Informatics Department in the Faculty of Natural, Mathematical and Engineering Sciences.

This is a full-time post (35 hours per week), and you will be offered a fixed-term contract until 31/07/2029.

About You

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

Essential criteria

• Undergraduate medical degree, and Master of Public Health or related field
• Demonstrable experience in AI/LLMs in healthcare contexts
• Experience of working in digital health research, from study protocol development to execution and data analysis, with a strong understanding of health data and personalised healthcare
• Evidence of writing peer-reviewed academic papers
• Demonstrable experience in medical or healthcare-related research, with evidence of interdisciplinary expertise combining medical and AI domains
• Strong understanding of natural language processing (NLP) techniques, including tokenisation, embeddings, and transformer architectures and familiarity with statistical methods and evaluation metrics for NLP models, such as F1-score
• Experience of developing digital therapeutics
• Excellent project management skills with the ability to initiate, plan, organise, implement and deliver programmes of work to tight deadlines

Desirable criteria

• Understanding of digital health platforms
• Ability or potential to contribute to the development of funding proposals in order to generate external funding to support research projects
• Knowledge of reinforcement learning techniques, particularly Reinforcement Learning with Human Feedback (RLHF), as applied to LLMs
• Awareness of regulatory frameworks in healthcare research, such as GDPR, HIPAA, or MHRA guidelines as relating to digital therapeutics and health AI

£44,355 to £51,735 per annum, including London Weighting Allowance