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. Supervise statistics collection and support our data tracking. Track and keep updated public information on our programs in relevant channels. Handle evaluations of our programmes. Assist the rest of the team
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DTU Compute is a unique and internationally recognized academic department with approx. 400 employees and 11 research sections spanning the science disciplines mathematics, statistics, computer science
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recognized academic department with around 440 employees and 10 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and
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biology, statistics, mathematics, computer science or related topics Advanced knowledge of Python and its scientific libraries and data stack (numpy, pandas, scipy, scikit-learn, pytorch, etc.) Proficiency
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unique academic environment spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research of high international standard that is at the forefront with
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). DynSys conducts research and provides teaching in the fields of mathematics, statistics, deterministic and stochastic modeling, optimization, forecasting and control. The section is very successful in
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of bioparts designs for low and high throughput implementation. Statistical analysis of internal and public datasets (e.g. genomics, transcriptomics, proteomics, metabolomics). Processing, visualization of NGS
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data sciences tasks like exploratory and statistical data analysis, training AI/ML models, or creating visualizations or dashboards using common industry frameworks and libraries. Programming in C, C