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statistical analysis and/or coding (e.g., R, Python, C++) Exposure to neurophysiological measurement methods (e.g., eye-tracking, pupillometry) Interest or training in technology law, digital regulation, or AI
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experiences in working with remote sensing data, climate data and programming skills (R or Python) are desired. You enjoy working in an international team and you are keen on developing a key set of research
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R Experience with single-cell RNA-sequencing, in particular analysis of data would be an advantage Experience with mouse models and possession of a FELASA B certificate would be an advantage as both
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to submit the dissertation after 3 years and 9 months of research. Desired requirements specific to this project include: experience with a range of relevant computer programming languages such as Python, R
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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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pressure Desired Practical experience in cell culture Practical experience in chemical analysis Experience in statistical analysis and programming languages, especially R What we can offer you Trust-based
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experience in chemical analysis Experience in statistical analysis and programming languages, especially R What we can offer you Trust-based working hours 30 days’ annual leave (5-day week) plus 24 and 31
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optimization. • Proficiency in programming (Python, R, Julia, or similar) and experience with frameworks like PyTorch, TensorFlow, or JAX. • Prior research in statistical learning and online optimization
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programming, modelling and data analysis skills in Python and/or R. Experience with the formulation and implementation of mathematical optimization problems can give you a competitive edge. The candidate should
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reports and contributing to scientific publications. Strong verbal and written communication skills for presenting experimental findings. Additional Considerations: Previous experience working in an R&D