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would be in addition to the normal employment and academic requirements of the student’s graduate program. Employment in this position would not reduce the work required as part of the graduate program
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: Sucessfully completed scientific university degree (Master) in the fields of chemical engineering, process engineering, chemistry or a comparable discipline Knowledge of hydrogen and energy research is an
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, Physics, Biotechnology, Microsystems Technology or a related field is required. Experience in one or more of the following areas: microfluidics, microscopy, fermentation, phototropic organisms, cell culture
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program. A doctoral degree or equivalent (Ph.D., ScD., DrPH, M.D., D.V.M., DDS etc) in Epidemiology, Biostatistics/Statistics, Bioinformatics, Genomics, or other relevant disciplines. Knowledge in the areas
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investigating the physical properties of the molecules in the laboratories on the campus of Forschungszentrum Jülich. The investigation of how these characteristics are influenced by processes in the value chain
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can also be used by NMBU in a possible admission process to the PhD program. Interviews with the best qualified candidates will be arranged. Applicants invited for an interview are expected to present
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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for physics beyond general relativity with gravitational-waves" (with Prof Eric Thrane) "Improving the sensitivity of gravitational-wave detectors" (with Prof Eric Thrane) web page For further details
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position will contribute to the research programme of the recently founded "AI Hub in Generative Models", a research consortium funded by EPSRC. The goal of the programme is to do research in the area of
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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs