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Field
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and Systems Biology develop and apply novel machine learning algorithms to detect patterns and statistical dependencies in large datasets from biology and medicine. Machine learning on graphs, machine
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molecular simulations, machine learning, statistical physics, multiscale modeling, and uncertainty quantification. The position is offered in the context of the EU funded project, aiming to develop a novel
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datasets, determination of ecological values based on statistical methods (e.g. PCoA, NMDS, TITAN), construction of microbial networks as well as trait-based models Presentation of project results
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, use-wear analysis, and controlled experiments. This combination of data requires a statistical tool for a transparent and reproducible workflow for data analysis and data modeling. By providing a
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in the Bachelor's and Master's degree programs of the Department, including the areas of statistics and methodology (8 weekly hours per semester). Teaching language is German. Supervision of students
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Economics, Economics, Data Sciences, Psychology, Statistics or a related field Evidence of research activity (publications) and/or future scholarly output (working papers, etc.) Proven interest in topics
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Leibniz-Institut für Agrartechnik und Bioökonomie e.V. | Potsdam, Brandenburg | Germany | 16 days ago
on statistical methods (e.g. PCoA, NMDS, TITAN), construction of microbial networks as well as trait-based models Presentation of project results at scientific conferences and stakeholder meetings, writing project
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University Hospital, incorporating data analytic tools such as statistics and machine learning. Your main tasks and responsibilities within this project are to: Conduct academic research which will lead to
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PostDoc in Chrononutrition (m/f/d) Department of Molecular Metabolism and Precision Nutrition (MMPN)
nutritional regulation of circadian clocks Planning and conducting of human studies in the field of chrononutrition and chronometabolic research Statistical and bioinformatic analysis of collected data and
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) methods, • with knowledge of statistics and ideally machine learning techniques (e.g., Natural Language Processing) and • excellent organizational and oral/written communications skills (command