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the following areas. You have a background in tissue-based molecular research and experience with tissue sectioning and the generation and analysis of spatial molecular data. Programming expertise in Python and R
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with an interest in ecological applications. Required qualifications: PhD (or equivalent) in computer science, biology, software engineering, or a related field Strong proficiency in Python, including
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, e.g., in Python, PyTorch, TensorFlow, or similar. Curiosity to work with researchers from a heterogeneous group, with core expertise in communication theory, networking, information theory, statistics
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systems, integrated sensing and communication, and theoretical modeling of 6G systems Solid mathematical background and significant experience in scientific computing programming (MATLAB, Python, C/C
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scientific programming, e.g. using Python, is expected. As we work in international environment it is important that you have a good communication skills in both spoken and written English, and experience in
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. The ideal candidate will have: Experience in developing novel algorithms. Experience in coding in python and preferably C/C++. Experience in frontend engineering, including but not limited
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materials, catalysis and/or surface science. For Topic 4, candidates must have documented skills within computational modelling of atomistic processes. Experience in scientific programming, e.g. using Python
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systems is an advantage. Basic to intermediate proficiency in Python, particularly for data analysis, modeling workflows, or automation, is desirable. Interest in electrochemistry, molecular modeling, and
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bioinformatic WGS data analysis and interpretation from bacterial isolates for AMR surveillance and/or genomic epidemiology. Proficiency in relevant bioinformatics tools and programming languages (e.g., Python, R
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computational chemistry or physics will be preferred, but candidates with a solid background in statistics, computer science, and/or mathematics are also encouraged to apply. Programming skills (e.g., Python