439 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions in United Kingdom
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of Edinburgh and Glasgow, with expertise across computer science, wearable computing, AI and criminology. Our programme of research utilises both experimental and literature-based approaches to explore
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disciplines may be eligible if they can demonstrate exceptional problem-solving skills and deep expertise computational model development. Candidates who have not yet acquired their PhD would be appointed
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to state-of-the-art facilities located within the thriving Department and will employ structural biology methods to address the group’s research questions. This is a full-time fixed term post funded by
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complex ideas, concepts and data using appropriate methods and packages To resolve issues and support colleagues in devising procedures required to ensure accurate and timely reporting To generate research
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Mobility Reading Group led by Nobuko Yoshida. The successful candidate will be located in the Department of Computer Science Reporting to Professor Nobuko Yoshida, the post holder will be responsible
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international initiatives. To be considered, you must hold, or be close to completion of, a relevant PhD/DPhil in one of the following subjects: computational genomics, genetic or molecular epidemiology, medical
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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to a project at the interface of research, policy, and international collaboration. The PDRA will gain experience in managing a complex bilateral programme, authoring outputs with direct policy impact
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analytical methods. Experience working with Mycobacterium tuberculosis or other Class 3 pathogens is essential, particularly in conducting infection studies using cell lines or clinical samples and in drafting
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-legal Studies, Science and Technology Studies (completed, or to be completed before post start date), or a cognate field. Experience of qualitative archival or interview-based research methods in a