Lecturer in Health Data Science Grade 8
3 months ago
We are seeking to appoint a Lecturer in Health Data Science to join an interdisciplinary research team of experts from academia, the NHS, local government, and industry. You will contribute to teaching (including development and delivery of CPD training), and research (bringing causal inference and machine learning/AI techniques) to mobilise data into action on prevention and early diagnosis, infection resilience, mental health and medicine optimisation.
This role will contribute to the new Data Action Accelerator, led by Professor Iain Buchan which brings people with complementary knowledge and skills about data and digital innovation together in a critical mass focused on NHS problem solving
- learning from each other in a secure NHS-led facility.
The team are now looking for an experienced and well organised individual who can contribute to the development of a teaching portfolio and your own research programme whilst contributing to the University strategic development as a leading member of the Civic Health Innovation Labs and the Department of Health Data Science.
Have a continuing record of teaching and research excellence which has contributed to the advancement of knowledge in health data science (with particular emphasis in causal inference and machine learning/AI techniques),
Be able to evidence ability to attract external research funding,
Have experience of working at the interface of academia and industry creating research ideas and approaches that aim to solve real-world challenges,
Bring experience of successfully supervising PhD students
Have a track record of academic leadership.
Be highly able, enthusiastic, and capable of inspiring those around you.
Collaborative working is essential, within CHIL and IPH, across the wider university and beyond.
This is a permanent post (conditional on Confirmation in Appointment after 3 years). When in the office, the role will be based in the Liverpool Science Park and/or the University Campus. Although the university has a hybrid working system, the expectation is that the successful applicant appointed to this role will be expected to work more than 50% on campus.
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