Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- University of Birmingham
- Nature Careers
- University of Leeds
- King's College London
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Leeds;
- University of Nottingham
- CRANFIELD UNIVERSITY
- Manchester Metropolitan University
- UCL;
- UNIVERSITY OF SOUTHAMPTON
- University of Liverpool
- University of London
- University of Manchester
- University of Oxford
- University of Surrey
- 7 more »
- « less
-
Field
-
, mechanistic simulations, and predictive AI models. Your work will help unlock new insights into disease mechanisms and inform potential treatments, diagnostics, and drug repurposing opportunities. Your role You
-
individually, make a real difference. The role Applications are invited for a Research Fellow position to support the design of a predictive health management (PHM) module for a novel steer-by-wire system aimed
-
of predictive AI models using multimodal data (e.g. time-series signals, neuroimaging, clinical records) for healthcare applications. Contribute to the development of a Digital Twin of the brain's motor system
-
and imaging for cancer research, with an emphasis on computational pathology to identify biomarkers predictive of treatment response, prognosis, and disease progression. The successful candidate will
-
to predict dormancy break. You will be part of a multidisciplinary academic and industry team of plant molecular biologists, geneticists, postharvest physiologists, agronomists, bioinformaticians, and
-
process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process analytical technology (PAT); process intensification
-
predictions to the experimental results of our partners from Salford and to include their experimental data for modelling vibrational sources and interconnections. We believe that talented and inclusive teams
-
the partnership, the Associate will develop the ability to: (i) model and predict fluid flow and system performance for large-scale systems; (ii) assess how different types of fouling may affect the membranes and