25 software-engineering-model-driven-engineering-phd-position-"Multiple" Postdoctoral positions at University of Cambridge
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research skills, and deliver seminars relating to the research area. The successful candidate should possess a PhD in Applied Analysis of Geophysical Fluid Models. Limit of tenure: 1 year in the first
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candidate will work with Professor Guilio Del Zanna on producing advanced atomic models. This post offers an excellent opportunity to contribute to a high-profile project focused on the development
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A position exists for a Post Doctoral Research Associate in the Department of Applied Mathematics and Theoretical Physics, funded by the High Energy Physics group's STFC Consolidated grant
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Engineering and a strong background in experimental magnetism. The position, based within Prof Jason Robinson's research group at the Department of Materials Science & Metallurgy, is part of the project
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(e.g., DFT modelling), or solid-state NMR spectroscopy. Excellent communication skills, a collaborative approach, and the ability to work independently are also key requirements for this position. A
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such as cancer biology, immunology, or genomics. Strong communication and collaboration skills are essential. Experience working with genetically engineered mouse models is desirable. Applicants
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evolution of a recently discovered family of clonally transmissible cancers which affect several species of marine bivalves. This new position is part of an ERC-funded project examining genome evolution in
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the cellular and molecular mechanisms driving tumour development. In this role, you will support a team of scientists using genetically engineered mouse models (GEMMs) and transplantable tumour models (e.g
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be about to obtain) a PhD in chemical biology. They will be highly motivated and able to work independently. Excellent organisational and interpersonal skills are required to ensure success in liaising
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with a multidisciplinary team of clinicians, data scientists, and data engineers to conduct epidemiological research on large-scale electronic datasets and develop common data model specifications