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investigating potential vaccination strategies for poultry. Methods from classical statistics, spatial statistics, machine learning and simulation modelling may be used as necessary to meet the objectives
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, Physics, Computer Science, etc.), a strong background in Data Science, Statistics, or Machine Learning, and an interest in Biomedicine. Alternatively, a candidate with a biomedical background with some
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.) for optimal operation using e.g. model predictive control. You will use stochastic and statistical modelling concepts together with domain-knowledge to develop such models. Afterwards, the models are used in
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the behaviour of fishes, particularly in the wild. Analytical skills and experience with statistical software (e.g. R, MatLab, Python) are expected as is experience in planning and executing fieldwork. Experience
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science(e.g., mathematics, physics, computer science, etc.), a strong background in data science, statistics, or machine learning, and an interest in biomedicine. Alternatively, a candidate with a
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will have the opportunity to influence the project based on their own ideas. Prior experience in working with fish in an experimental context is considered an asset, and proven skills in statistical
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trials Accuracy and patience for laboratory work Experience with UPLC and Western Blotting Analytical skills and experience in statistical analysis Strong written and oral communication skills in English
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on generative AI have been suggested. The data science team under this project will develop privacy metrics based on Bayesian statistics. The overarching purpose of the legal part of the project is to develop
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) for ongoing lab projects. The candidate should have a two-year master’s degree in Bioinformatics, Computational Biology, Biostatistics or in a related quantitative field (e.g. Mathematics, Physics, Statistics
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theoretical aspects of machine learning. Therefore, a sufficient background in mathematics (e.g., linear algebra, statistics, optimization, calculus) is expected, along with programming experience using deep