Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- ;
- KINGS COLLEGE LONDON
- King's College London
- University of Cambridge
- University of London
- Durham University
- AALTO UNIVERSITY
- DURHAM UNIVERSITY
- Heriot Watt University
- UNIVERSITY OF VIENNA
- University of Liverpool
- University of Birmingham
- Nature Careers
- ; University of Copenhagen
- Imperial College London
- Medical Research Council
- Swansea University
- University of Manchester
- University of Oxford;
- ; Royal Holloway, University of London
- ; Technical University of Denmark
- ; University of Cambridge
- ; University of Dundee
- Aston University
- Birmingham City University
- Heriot-Watt University;
- King's College London;
- Manchester Metropolitan University
- Nanyang Technological University
- Queen Mary University of London
- Royal College of Art
- Sheffield Hallam University
- The Royal Veterinary College, University of London;
- University of Cambridge;
- University of Glasgow
- University of Hull
- University of Leicester
- University of Lincoln
- University of Newcastle
- University of Reading
- University of West London
- 32 more »
- « less
-
Field
-
Associate with mathematical modelling and numerical/data analysis background to join our food system resilience project, led by University of Reading, joining a large interdisciplinary team with an excellent
-
including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
-
expertise in analysing/ training models on biological or chemical datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
-
About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
-
About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
-
help develop and characterise advanced patient-derived tumour models and use them to test promising therapeutic targets that exploit vulnerabilities caused by loss of the SMARCB1 gene. This role offers
-
experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
-
Agency (ARIA). The PROTECT project (Probabilistic Forecasting of Climate Tipping Points) brings together cutting-edge AI, statistical, and machine learning techniques with climate modelling, aiming
-
samples and disease models. Working closely with a dynamic and multidisciplinary team of clinicians and scientists, you will help generate and interpret high-resolution datasets that reveal new insights
-
experimentation, applying state-of-the-art single-cell multiomic approaches and functional genomic screens to patient-derived samples and disease models. Working closely with a dynamic and multidisciplinary team