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engineering, and have a strong background in numerical analysis and scientific computing. Required qualifications include basic knowledge of numerical methods for PDEs, expertise in High Performance Computing
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will be supported by our extensive battery testing facilities, including equipment for commercial cells, half- and three-electrode measurements, and advanced materials analysis. About the research group
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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get
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research projects, as evidenced by scientific publications in internationally peer-reviewed journals - Good knowledge in genomics, bioinformatics and experience in statistical analysis of large datasets
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experiments, cutting-edge NMR spectroscopy and isotopomer analysis (doi: 10.1111/nph.20358). Two postdocs will work together to conduct plant ecophysiology experiments, and to analyze samples by NMR
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experience in project design, analyses, interpretation and scientific publication and be involved in a project that develops future AI tools for genomic analysis. Examples of areas in which the scholarship
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analysis, Python programming, and deep learning frameworks (e.g., TensorFlow, PyTorch) is expected. Prior work in cancer research or medical imaging is an asset. The successful candidate will join an
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method development, and various molecular biology and biochemical analysis techniques. You should also have a strong research track record, as evidenced by first authorship publications in relevant
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integrated structural biology and biochemistry. You should have hands-on experience with cloning, protein expression and purification. Experience in biochemical / biophysical analysis of membrane proteins and
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monitoring will be particularly useful. A solid background in statistical data analysis and previous experiences with catchment hydrochemical modelling are merits. Excellent English skills, both in speaking