Lecturer or Senior Lecturer in Health Data Science and AI

King's College London


Job description

We are seeking an innovative, enthusiastic and committed Lecturer or Senior Lecturer in Health Data Science and AI, to grow the department’s capacity in the area and deliver high-quality research and teaching.   

We expect the appointed person to show exceptional promise, to develop rapidly and to have the potential to be a national leader in Health Data Science and AI. 

The post holder will take a leadership role and work closely with the new incoming Head of the School & Chair in Population and Digital Health Sciences, Professor Josip Car, to strengthen and lead a Health Data Science and AI programme in the School. The postholder will also be part of the Digital Health Group in the Department of Population Health Sciences.

The new appointee will develop insights, solutions, methods, and practice through application of Data Science and AI to health and medical sciences, leading methodological developments and collaborating with researchers across the School and King’s.  Their research will embrace explainable AI, computational phenotyping, digital guidelines, generative AI, and large language models (LLM).  The successful candidate will conduct high-quality, reproducible, and comprehensive analyses of large clinical and routine datasets (Clinical Practice Research Datalink, Hospital Episode Statistics, Lambeth DataNet), as well as individual data from wearables, mobile devices and social networks (e.g., related to development of novel digital biomarkers).  Of particular interest are the applications of these technologies to the challenges of managing multimorbidities in aging populations and links between non-communicable diseases and mental health, both in UK and global settings. 

The post holder will also contribute to the development and delivery of Health Data Science and AI education and training for undergraduate and postgraduate courses in medicine and population health. They will lead on the development of new, innovative, co-created, postgraduate courses in Health Data Science and AI, using the potential of London as a living laboratory.  

The post holder will develop excellent networks across the School of Life Course & Population Sciences (SLCPS) and be a collegial collaborator, both in teaching and research.  They will support early career researchers to develop teaching portfolios and participate in a variety of research teams.  They will need to attract significant research income as PI or Co-I and deliver a growth agenda in one or more areas of Health Data Science and AI that supports research within SLCPS and the Faculty of Life Sciences and Medicine. 

The Lecturer will receive excellent support for career development including time for technical, academic and professional development courses, personal mentoring and conference attendance. 

This post will be offered on an indefinite contract. 

This is a full-time post – 100% full time equivalent.

Key responsibilities

  • Conduct cutting-edge research in Health Data Science and AI, contributing to the School’s profile and securing external funding.  
  • Develop and implement new programmes, courses, and initiatives related to Health Data Science and AI, ensuring alignment with research and industry trends. 
  • Supervise and mentor undergraduate, postgraduate, and research students, fostering a supportive learning environment. 
  • Collaborate with academic colleagues, industry partners, and other stakeholders, including NHS partners, to advance knowledge and application of Health Data Science and AI. 
  • Actively participate in departmental and university-wide committees, working groups, events, and Athena SWAN activities, contributing to continuous improvement and promoting equal opportunities. 
  • Maintain up-to-date knowledge of developments in Health Data Science and AI, incorporating them into teaching, research, and outreach activities.  
  • Publish regularly in peer-reviewed journals, present at conferences, and exhibit work at appropriate events to disseminate research findings. 
  • Develop, disseminate, and maintain tools and research software, fostering a culture of open-source collaboration. 
  • Contribute to student recruitment, secure placements, facilitate outreach, generate income, and build relationships for future collaborations and partnerships. 
  • Continuously update and refine teaching methods, materials, and curriculum, incorporating research findings and feedback from students. 
  • Contribute to administrative tasks, such as admissions, examinations, assessments, and monitoring student progress. 
  • Perform any other duties commensurate with the grade and purpose of the position, as required. 

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.  

Lecturer (Grade 6)  

Essential criteria

1.      PhD in population health, epidemiology, biostatistics, data science, computer science, health analytics, or related field. 

2.      Relevant research experience in the development and application of methods for large, complex, health-related data, such as electronic medical records, and/or digital and mobile health data and statistics. 

3.      Proven track record of high-quality and translatable research in the general area of artificial intelligence, statistical machine learning, data fusion and signal processing applied to medical problems, or in information engineering aspects of healthcare informatics. 

4.      Proficiency in programming languages and statistical analyses. 

5.      Evidence of excellent capability for analyses of large datasets. 

6.      Track record of collaboration. 

7.      Committed to equality, diversity and inclusion, actively addressing areas of potential bias. 

Lecturer (Grade 7)

Essential criteria 

1.      PhD in population health, epidemiology, biostatistics, data science, computer science, health analytics, or related field. 

2.      Relevant research experience in the development and application of methods for large, complex, health-related data, such as electronic medical records, and/or digital and mobile health data and statistics. 

3.      Proven track record of high-quality and translatable research in the general area of artificial intelligence, statistical machine learning, data fusion and signal processing applied to medical problems, or in information engineering aspects of healthcare informatics. 

4.      Proficiency in programming languages and statistical analyses. 

5.      Evidence of excellent capability for analyses of large datasets. 

6.      Track record of collaboration 

7.      Committed to equality, diversity and inclusion, actively addressing areas of potential bias. 

8.      Evidence of successful independent, high-quality research (or evidence of a trajectory towards this), including evidence of publications of high-quality, peer-reviewed papers. 

9.      Evidence of successful research grant applications as Co-Investigator. 

10.    Experience in the development and/or delivery of high-quality teaching. 

Senior Lecturer (Grade 8)

Essential criteria

1.      PhD in population health, epidemiology, biostatistics, data science, computer science, health analytics, or related field. 

2.      Relevant research experience in the development and application of methods for large, complex, health-related data, such as electronic medical records, and/or digital and mobile health data and statistics. 

3.      Proven track record of high-quality and translatable research in the general area of artificial intelligence, statistical machine learning, data fusion and signal processing applied to medical problems, or in information engineering aspects of healthcare informatics. 

4.      Proficiency in programming languages and statistical analyses. 

5.      Evidence of excellent capability for analyses of large datasets.  

6.      Proven successful independent, high-quality research including evidence of publications of high-quality, peer-reviewed papers.  

7.      Track record of excellence in national collaboration. 

8.      Evidence of substantial research grant income as Co-Investigator as well as Principle Investigator.  

9.      Experience in the development and delivery of innovative learning activities, teaching materials and methods of assessment.   

10.    Committed to equality, diversity and inclusion, actively addressing areas of potential bias. 

We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.  

The School of Life Course & Population Sciences is one of six Schools that make up the Faculty of Life Sciences & Medicine at King’s College London. The School unites over 400 experts in women and children’s health, diabetes, nutritional sciences, population health and the molecular genetics of human disease. Our research links the causes of common health problems to life’s landmark stages, treating life, disease and healthcare as a continuum. We are interdisciplinary by nature and this innovative approach works: 93 per cent of our research submitted to the Subjects UoA 2 (Public Health, Health Services and Primary Care) and UoA3 (Allied Health Professions, Dentistry, Nursing and Pharmacy) was rated as world-leading or internationally excellent in REF 2021.We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across six Departments. 

More information: https://www.kcl.ac.uk/slcps

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