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Solid experience with statistical modeling, machine learning, or AI Practical skills in R and/or Python for data analysis and model development Familiarity with microbial ecology, genomics, or food safety
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– Department of Mathematics and Computer Science – is an internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics
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science, statistics or a related field. Please note that your master’s degree must be equivalent to a Danish master’s degree (two years). Other important criteria are: The grade point average achieved Professional
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work with fish and/or aquaculture systems Accuracy and patience for laboratory and experimental work Interest towards statistics and bioinformatics Strong written and oral communication skills in English
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The Department of Civil and Mechanical Engineering of the Technical University of Denmark (DTU) has an open PhD position (3 years) on the topic of “Automated machine polishing of complex mould geometries”. The position is funded in the context of the project MADE React co-funded by the...
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used will be Density Functional Theory, statistics, machine-learning and dynamics. Collaboration with members of other research groups at UCPH and abroad is required. Who are we looking for? We
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algorithmic aspects of cheminformatics. The position is founded by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases ”, led by
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of technological advancements, and we're excited to include more brilliant minds in our journey. See our publications and projects here . DTU Compute – Department of Mathematics and Computer Science – is
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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systems Documented knowledge in power and energy markets preferably Nordic and European markets Documented knowledge in dynamic modelling of power system Knowledge of mathematical optimization. Knowledge