848 parallel-and-distributed-computing-phd Fellowship research jobs in United Kingdom
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; or Experience with high-fidelity solvers, e.g. SU2, OpenFoam, StarCCM+, Fluent; Proficiency in programming, e.g. Python, Matlab, C; Experience utilizing high-performance computing (HPC) to parallelize workflows
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, Integrate the DNAm datasets with longitudinal eHealth records to build epigenetic signatures of healthy ageing, which we will then track longitudinally in parallel with other hallmarks of ageing using six
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for large samples at ESRF ID16A using multislice tomography approaches. You will lead the development of and work with parallelized computer models to simulate how coherent waves travel through materials with
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● PhD in computational biology, bioinformatics, statistical genetics, genomics, or a related field ● Publication record demonstrating experience in high-quality computational research ● Proven ability
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The job details are shown below. For further information click on the link for the job description. About the role The School of Engineering, Computing and Mathematics (SECaM) wishes to recruit a
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the direction of a strategically important research area. We hope you will bring: We are looking for a candidate with a PhD in Electrical Engineering, Computer Science, Economics, or a closely related field, and
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expertise in all communication and broadcasting systems and has developed the best in class large scale testbeds for research and innovation and enjoys the state-of-the-art lab and computing facilities
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8 Nov 2025 Job Information Organisation/Company UNIVERSITY OF SURREY Research Field Computer science Engineering Researcher Profile First Stage Researcher (R1) Country United Kingdom Application
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8 Nov 2025 Job Information Organisation/Company UNIVERSITY OF SURREY Research Field Computer science Engineering Researcher Profile First Stage Researcher (R1) Country United Kingdom Application
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. An MSC in statistics with expertise in causal inference would also be acceptable if the student is willing to complete a PhD. Experience in causal inference techniques such as g-computation, and propensity