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master's degree or equivalent education in computer science or related fields (for instance mathematics, statistics, medicine with a strong emphasis on computational and programming aspects). Experience in
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(for instance mathematics, statistics, medicine with a strong emphasis on computational and programming aspects). Experience in machine learning is a requirement. Experience with programming and app development
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for applications. Applicants must have obtained at least a master's degree or equivalent education in computer science or related fields (for instance mathematics, statistics, medicine with a strong emphasis on
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on these hypercubic inference approaches, and several members in clinical research dealing with the clinical data. Training will be provided on these methods, and the applicant should have experience with statistical
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within (bio)statistics, bioinformatics, applied mathematics, computer science or a related quantitative discipline , or must have submitted his/her doctoral thesis for assessment prior to the application
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strong background in statistics is required. Experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages is required. Experience with AI-related
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statistics is required. Experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages is required. Experience with AI-related research and/or
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learning: mathematical foundations, (probabilistic) learning algorithms, performance measures, metrics, visualization, statistics, downstream tasks such as dimensionality reduction or generative modelling