136 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at King's College London
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
well as Machine Learning (ML) tools — to interrogate a very large sample of Electronic Health Records from people with epilepsy across multiple NHS hospitals. They are expected to have experience working in Data
-
the role The PDRA will carry out research on probabilistic circuits (PCs) and tree-based machine learning methods for generative modelling, with a particular focus on responsible AI. The project builds
-
lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning techniques—including vision-language architectures (e.g., CLIP
-
CANDIDATES ONLY About Us The applicant will join the Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. We are a highly collaborative
-
for King’s Engineering. We offer undergraduate and postgraduate education, with a distinctive approach, combining traditional teaching methods with modern, project-based learning, catering for the needs of our
-
, machine learning, multiscale and multiphysics simulation, computational anatomy, medical image analysis, and integration of wearables and biosignal processing, applied to conditions ranging from cardiac
-
science. The successful candidate will be appointed to the Cybersecurity (CSY) group, where our work on cryptography sits, and will have the opportunity to contribute to cross-cutting hubs (see https://www.kcl.ac.uk
-
sets out the actions that we must take to transform how we teach, how and where our students learn and how we support them during their time with us. King’s Careers & Employability (KC&E) empowers over
-
focused on hands-on AI development, including topics such as: Programming for AI (e.g. Python-based workflows, data pipelines, model training and evaluation) Applied machine learning and deep learning
-
Professor Nicola Fear, CBE. For more information, please see https://kcmhr.org KCMHR in partnership with RAND Europe runs the Centre for Evidence for the Armed Forces Community, funded by the Forces in Mind