77 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Linköpings-University" positions at King's College London
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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
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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
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. We are looking for a computer scientist with expertise in both front-end and back-end development. Specifically, the objectives of the post holder will be to develop a smartphone app to instruct
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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
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About us: We are seeking to appoint a postdoctoral research associate with an excellent track record in semantic technologies and machine learning. Topics of interest in this area include, but
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demonstrable ability to learn relevant technologies 5. Logical and methodical approach to problem solving and technical troubleshooting 6. Strong customer service ethos (able to cater for technical
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as trainers and observers in the GMP cleanrooms. The post holder will learn a wide range of molecular and cell biology skills such as cell culture, transfections, QPCR, flow cytometry etc. They will
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, and human-centred computing. You will join the Vision & Human-Robot Interaction (VHR) Lab, a multidisciplinary research group working at the intersection of robotics, machine learning, and human
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: Essential criteria Be enrolled in or hold a first degree in biomedical engineering, robotics, or relevant discipline. Possess sufficient specialist knowledge in computer aided design, systems integration, and
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are caused and how people respond to treatments. We will investigate blood and cerebrospinal fluid from patients and use machine-learning to identify the treatment-relevant immune processes, with an emphasis