-
. The candidate will also have experience of psychophysiological methods, preferably EEG or MEG, and strong quantitative and programming skills in time series analyses using Python/MATLAB (or equivalent
-
development, research delivery, and dissemination; leading/supporting grant applications to prestigious funders; contributing fully to our ARC Academy training programme. The postholder will also support the
-
possible. We strive to ensure the diversity of our candidates, and we reflect this ethos in the way we promote the ICRF programme and in our recruitment and selection process. Imperial’s diversity networks
-
already commenced training in general cardiology and wish to gain more sub-specialty experience in Cardiac MRI (CMR), by taking an Out-Of-Programme Experience (OOPE) from their current training programmes
-
Mission. You will deepen UKERC’s research capabilities, complementing existing strengths. You will build on a successful programme of activity focused on risk and investment in energy markets, working
-
research clinicians concerned with both basic immunological principles and understanding the immune response through treatment. The post holder will be based within the largest CAR T cell program in Europe
-
and Supporting Distance Dementia Care (CONSIDER). CONSIDER is an 18-month research project funded by the NIHR Research Programme for Social Care. The project aims to understand and provide
-
%. Health & Well-being: 24/7 GP consultation services. Occupational health services and mental health support programs. Eye care vouchers and discounted healthcare plans. Work-Life Balance: Back-up care for
-
Epidemiology or related subject or a similar quantitative discipline. Programming skills in Python; or experience in at least one of the following: C, C++, Java, R, Matlab, and willingness to learn Python
-
, computational biology, computer science, data science or a related subject area and proven knowledge of python programming, developing machine learning/AI based tools and HPC. You will be expected to work as part