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hiring date is as early as December 1, 2025, but can be anytime in 2026. The PhD student is expected to develop and apply statistical methodology for causal inference in observational and experimental data
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the carbon footprint of milk production. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision
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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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with a wide range of data formats and engaging with data experts and database managers. The second major focus is advanced data analysis and statistical modeling to identify patterns in fish distribution
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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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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working with live animals. Excellent skills for data handling and statistical analysis. Strong written and oral communication skills in English. Ability to work both independently and as a part of a team
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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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degrees in either the natural sciences (chemistry, physics, mathematical/computational biology) or in the formal sciences (statistics, computer science, mathematics), but must have a serious interest in