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concerning the detection of casewise and cellwise outliers using robust statistical methods. This project is within the thematic field “Robustness in complex data analysis and statistical modelling
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experiments will be mainly performed in rodents, you hold a FELASA certificate (or equivalent), or you are willing to obtain one. You have basic knowledge of statistical tools. Your teaching competences are in
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Master in Experimental Psychology, HCI, UX or related fields Experience with research methods in social sciences (e.g., empirical research, experiment design) Experience in statistical methods is
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(-renewable) Profile: PhD Reproductive medicine background Experience in immunohistochemistry, molecular biology (miRNA) and cell & tissue imaging Autonomy in statistics and data management FELASA-B certificate
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conducting biodiversity research at different levels. MSc/Diplom (DE) in a field related to ecology (e.g. pollination, chemical or molecular ecology). Strong experience with statistical data analyses
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position, you must meet the following requirements: Hold a relevant master’s degree or an equivalent higher education qualification in fields such as Computer Science, Artificial Intelligence, Statistics
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position, you must meet the following requirements: Hold a relevant master’s degree or an equivalent higher education qualification in fields such as Computer Science, Artificial Intelligence, Statistics
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, will serve as input to generate a statistical prediction model, that will be built together with the bioinformatics team. You will publish scientific articles related to the research project, disseminate
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related field. Interest in energy markets, digital technologies, policy analysis, or regulatory frameworks. Strong quantitative and qualitative analytical skills. Proficiency in statistical software such as
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of different energy sources using tailored statistical metrics and indices Publish results in peer-reviewed journals, present findings at international conferences, and collaborate with project partners