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Field
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mentoring junior researchers and contributing to a positive and inclusive lab culture is highly valued. Experience with R or Python is an advantage, but candidates with a strong willingness to develop
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skills in R and/or Python Experience analysing complex biological datasets A clear scientific vision on precision nutrition and integrative data approaches Preferably, you also have: Experience with
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in a relevant field (e.g., computational linguistics, digital humanities) Excellent programming skills, with extensive experience in Python Extensive experience with recent Python-based machine
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diffusion models Familiarity with CT imaging workflows or radiological image-analysis pipelines Ability to develop reproducible research code in Python, preferably using PyTorch Experience with explainable AI
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for early drug discovery Basic coding skills (e.g., Python, KNIME, or similar) A strong publication record in peer-reviewed journals Scientific curiosity, creativity, and a goal-oriented research mindset
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several—of the following: policy analysis, survey research, quantitative analysis, scientometrics, stakeholder co-creation. Advanced proficiency in R and python for statistical and corpus analysis Ability
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quantitative skills (e.g. advanced statistics, programming in Python, R, or Matlab). You have experience with neuroimaging and/or computational modelling of cognition and behaviour (e.g. reinforcement learning
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Expertise: Deep experience in Large Eddy Simulation (LES) and a solid understanding of Atmospheric Boundary Layer (ABL) physics. Programming: Strong proficiency in C++, Fortran, or Python, and experience
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. You are motivated to conduct applied research in close collaboration with industry partners and SMEs. You have a track record of scientific publications in relevant venues. You are proficient in Python
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collaboration with industry partners and SMEs. You have a track record of scientific publications in relevant venues. You are proficient in Python and relevant machine learning frameworks such as PyTorch