23 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions at King's College London
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techniques Experience in protein expression and purification methods Good understanding of structural and molecular biology and biochemistry * Please note that this is a PhD level role but candidates who have
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working effectively as part of a multi-disciplinary research team. An enthusiasm for healthcare data research and willingness to adapt and learn new research methods. Desirable criteria Knowledge
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work make a real-world impact? King’s College London is seeking a talented Postdoctoral Research Associate to join the pioneering NanoCure project, an ambitious programme developing medical-grade
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of study. They will have prior research experience of computational approaches and must also be able to demonstrate sufficient knowledge of the discipline, as well as research methods and techniques, to work within
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-delivered systemic anti-cancer therapies. It requires a unique blend of expertise in pharmaceutical science, drone piloting, and analytical methods. The postholder will contribute to pioneering approaches in
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criteria PhD in research methodology, social sciences, or a closely related field (or near completion). Demonstrated experience in participatory, visual embodiment, and interpretive research methods. Track
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the use of computing servers Desirable Criteria Experience fine-tuning large language models (e.g., BERT, BioGPT, MedPaLM) for clinical NLP tasks. Experience with cloud or distributed computing environments
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the Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences (NMES). The department is internationally recognised for its contributions to robotics, AI, and human-centred
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers) for academic research Documented experience in