111 parallel-computing-numerical-methods-"Simons-Foundation" positions at Nature Careers in United Kingdom
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to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research project. We are looking for a Research Fellow to work in the area of
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Contribute to developing new models, techniques and methods Person Specification First degree in Chemistry and normally, a higher degree relevant to research area or equivalent qualifications/experience
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proteins. Experience with cell-based experimental systems, including mammalian cultured cells and with in vitro reconstitution methods, especially as they relate to membrane proteins is required. Other
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data and identify appropriate costs. Develop or adapt techniques, models and methods (as appropriate). Contribute to the analysis and interpretation of qualitative and quantitative data. Assist with
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program. Through this work, you will build scientific independence, develop new science and leadership skills, and establish a growing reputation externally. Your role will be to lead a research project
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are particularly welcome. AI/ML approaches are of growing importance in all areas and we encourage pioneers of these methods to apply. The positions are open to candidates whose research and teaching is focused
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to publications Main Duties Collect research data; this may be through a variety of research methods, such as scientific experimentation, literature reviews, and research interviews Analyse research data as
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axon development. However, these methods lack the resolution needed to analyse axon branching and synapse formation. This project aims to establish a high-resolution imaging pipeline by incorporating
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will develop and apply methods to transform omics data into networks and executable models, collaborating closely with experts across the Petsalaki and Sheriff groups, Open Targets, EMBL-EBI, and the
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have access to ICR’s successful PhD training programme and core facilities. Key Requirements Higher degree (MSc or PhD) in medical statistics/biostatistics or an allied field (e.g. public health