KINGS COLLEGE LONDON

AI Specialist

Location
London (Central), London (Greater) (GB)
Salary
Grade 7, £46,292 to £53,053 per annum, inclusive of £3,500 per annum London Allowance
Posted
Aug 04, 2020
End of advertisement period
Aug 30, 2020
Ref
R7/0845/20-KA
Contract Type
Fixed Term
Hours
Full Time

In collaboration with a major pharmaceutical partner, King’s College London is launching a substantial programme of basic and translational research into understanding the early molecular and immunological events that lead to the establishment Clonal Haemopoiesis and early stages of Myelodysplastic Syndrome (MDS). Comparison of these early events with subsequent molecular phenotypes of MDS and Acute Myeloid Leukaemia (AML) should help to identify targets for therapeutic intervention. It is anticipated we will recruit over 6,000 patients undergoing hip replacements as a healthy ageing cohort for the study to follow for at least 5 years; continuing to observe changes to health and haematology profiles. The programme aims to build one of the largest Biobanks to interrogate associations between immune and genetic changes in the blood and diseases that increase in prevalence with age and to enable future translational research endeavours. There is therefore an urgent need to develop reliable tools for patient stratification in order to ensure that only those likely to benefit are given a specific treatment.

Artificial Intelligence (AI) methods have recently gained a lot of momentum in terms of applicability in different academic and industrial areas. In particular, in the context of this project, which needs an integrated clinical bioinformatics platform, AI can be quite valuable not only in modelling clinical and bioinformatics data but also for making and/or helping scientists to make new discoveries. Therefore, the post holder is expected to provide the-state-of-the-art solutions for data integration and analysis, designing and applying novel visual analytics methods, software prototyping and development, technical supervision of the students, and training of new users on applications of machine learning techniques for cancer studies. The post holder will also be responsible to interact with other biology and clinical labs and their corresponding students/postdocs for both delivery and interpretation of the data.

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