14 computational-physics-"https:"-"https:"-"https:"-"IMEDEA-CSIC-UIB" Fellowship positions at King's College London
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THIS VACANCY IS OPEN TO INTERNAL CANDIDATES ONLY About Us We are seeking a highly motivated and experienced researcher to work on the large-scale programme and associated projects of the Data
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, computer science, and the natural sciences to develop the conceptual and mathematical tools needed for the trustworthy deployment of AI agents in science. The project is based at the Egenis Centre for the Study of
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, and with expertise in quantitative and qualitative methods, to develop a training and capacity-building programme and lead research projects working on large datasets. On training and capacity-building
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conferences in areas of machine learning, computer vision, and Large Language Models and high-impact specialist peer reviewed academic journals. • Ability to conduct interdisciplinary research activities
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meshworks are shaped, constrained, and canalized How nuclear integrity is maintained in a developing, beating heart Physical principles of organ scaling and regeneration The role of bioelectricity in
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part of an EPSRC Programme Grant involving 15 co-investigators in a range of disciplines related to development of PET imaging strategies for the development of healthcare nanomaterials for therapeutic
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), based within the Department of War Studies at King’s College London, is seeking a Research Fellow for its new Net Assessment Programme. They will be engaged on a new multi-year research project funded by
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assessed at each stage of the recruitment process. Further Information At King’s, we believe that the diversity of our community and a culture that is welcoming, open, inclusive and collaborative, are great
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projects, and contributing to the preparation of research proposals. The role involves conducting independent and collaborative research, identifying potential funding sources, and supporting the process of
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clinical base at the Maudsley Hospital and involves affiliated laboratories across King’s Health Partners. The programme is strongly lead by statistical modelling to predict not just Parkinson’s disease (PD