19 parallel-computing-numerical-methods Postdoctoral research jobs at University of Cambridge in United Kingdom
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methods, with a breadth of conceptual knowledge in historical sociology. You will have research expertise in historical studies of empire, colonialism, and/or anti-colonialism evidenced through doctoral
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in Cambridge. The mission statement of the group is "developing statistical methods to use genetic variation to answer clinically important questions about disease aetiology and prevention". The three
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modelling to study the causes and consequences of extreme chromosomal instability in these cancers. The role will involve: - Learning and applying cytogenetic methods for generation and analysis of chromosome
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to develop and improve current simulation methods (quantum and classical) to study such systems. The overarching aim of the post-doctoral position is to develop and apply computational approaches that enable
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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at the Yusuf Hamied Department of Chemistry, University of Cambridge to work on the BBSRC grant "A Platform for Identifying GlycoRNA and Identifying Biases in RNA Pulldown". The role is to develop methods
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techniques. Analyse experimental data using statistical tools and computational methods. Collaboration & Mentorship: Collaborate with interdisciplinary teams of researchers and students. Mentor graduate and
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application of comprehensive polar metabolite analysis methods. Scientists are encouraged to apply if they have substantial practical experience in the development of comprehensive quantitative methods
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bioinformatics/computer science will be essential. Prior experience with connectomics data is highly desirable. Our group has developed an international reputation in this area and our tools have now been used in
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-generation AI hardware (ASIC) accelerators. The UK's Advanced Research Invention Agency (ARIA) is supporting an ambitious programme of work that aims to reduce the the cost of AI by more than 1000x: https