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Field
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, mathematics, and innovation. Candidates must hold (or be close to completing) a Ph.D. in Applied Mathematics, Electrical or Mechanical Engineering, Physics and Applied Physics or a related field. Working in a
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degree and PhD degree in meteorology, oceanography, physics or mathematics, with a strong interest in the application of statistical and data analysis methods excellent knowledge in UNIX/Linux and Unix
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understanding and knowledge of climate dynamics. The candidate should have experience of statistical (multivariate) concepts and should be open to apply new and upcoming AI methods to analyze the climate
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that regulate B cell activation, antibody production and their genetic variability. We use a wide range of immunological and genomic assays to study B cell biology, antibody diversity and variation in the human
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determined by the funding available. About you You should hold, or be near completion of, a PhD/DPhil in Molecular Microbiology, Biochemistry, Biophysics or related discipline. You must have substantive
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, Bioengineering, Biophysics, Biostatistics, Mathematics, Statistics, Electrical Engineering, Biomedical data science, etc; Candidates with multidisciplinary backgrounds are also welcome. Strong skills in
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Technology and Production Automation, m.cao@rug.nl We are looking for candidates who meet the following requirements A PhD degree in Control Engineering, Applied Mathematics, environmental Psychology or a
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, Computational Biology, Applied Mathematics or related field Interest in interdisciplinary research Applied experience with machine/deep learning methods Ability to handle multiple projects in a dynamic
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for a hard-working candidate. Qualifications Required skills A PhD degree within statistical genetics, applied mathematics, computer science, medicine, psychology, molecular genetics, or similar. Advanced
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, systems biology, applied mathematics, nuclear medicine physics, or a related field. Prior experience in at least one of the following is a requirement: physiologically based pharmacokinetic (PBPK) modeling