20 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions at University of Cambridge
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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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the starting date is negotiable. The current funding is guaranteed from the Montague Burton Fund. We are looking for a candidate who is a health economist with excellent computational skills. The post is
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research centre well-known for its close-knit community, friendly atmosphere, and outstanding research support. We are seeking a post-doctoral research associate with experience in computational approaches
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of the research programme is to develop EHR common data model specifications and to advance knowledge in the field of psychiatry EHR research, including clinical risk prediction modelling. The appointee will work
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to the regulation of complex behaviours. This will involve a range of techniques including high resolution confocal microscopy to determine receptor localisation, behavioural analysis of C. elegans and computational
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situ/operando experiments and associated cell design is desirable. Familiarity with one or more of the following techniques is highly desirable: X-ray and neutron diffraction, computational chemistry
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enable the full exploitation of next-generation observations using Exascale computing, i.e. leading the research in solar/stellar physics for many years to come. We are seeking a highly motivated Research
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Mathematics and Mathematical Statistics. Duties include developing and conducting an individual program of research. The successful candidates will usually be associated with one of the departmental research
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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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