163 parallel-and-distributed-computing-phd Postdoctoral positions at University of Oxford
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PhD or be near completion, in physics, mathematics, computer science or a related discipline, and possess sufficient specialist knowledge in the discipline to work within established research programmes
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. They will be expected to guide more junior colleagues, including postdocs, research assistants, PhD and project students. The research may involve either analytical work, numerical computations or both
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computational pipelines suitable for downstream integrative and AI-driven discovery. The role includes training PhD students, contributing to grant applications, project planning, and leading the preparation
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opportunity to teach. Applicants should possess or be close to obtaining a PhD in physics, materials science, or physical chemistry. They should be highly experienced in advanced first principles computational
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research projects, contributing to major funding applications, publishing high-impact research, and mentoring junior researchers. Applicants should hold a PhD/DPhil in cell biology, cancer biology, computer
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for carrying out research on the European Research Council Project METACOMP on “Meta-Complexity: A Unified Approach to the Complexity of Proofs and Computation”, with Rahul Santhanam as Principal Investigator
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. Applicants should hold a PhD in computational biology, bioinformatics, systems biology, computer science, or a related quantitative discipline, with relevant postdoctoral research experience. Demonstrated
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be determined by the funding available. About you You will hold or be near completion of a PhD/DPhil in Computational Biology, Bioinformatics, Genomics, or a closely related field, with significant
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, participating actively in group discussions, and potentially contributing to undergraduate or graduate teaching. Applicants should hold (or be close to completing) a PhD in computational/theoretical chemistry
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The postdoctoral researcher will lead the development of computational methods for aligning cortical organisation across species using transcriptomic and anatomical data combined with modern machine