186 computer-science-intern "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Leibniz
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interface of science and practice, Excellent infrastructure for scientific work, Access to national and international networks for your scientific development, Training and further education opportunities
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and cooperation with national and international researchers and within the team of LIfBi Department “Competencies, Personality, Learning environments” Contributing to analyses and the preparation
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research project “Cities. Building. Culture – The Residential Heritage of the Soviet Union in Times of Multiple Crises” funded by the Federal Ministry of Education and Research (BMBF). This international and
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proposals, scientific publications, statistical and project reports Your profile: University degree (PhD) or any other equivalent combination of education in epidemiology related sciences, including
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plasma cells within specific regions of the bone marrow. Requirements and Skills: Excellent M.Sc. degree (or equivalent) in the areas biomedical, computational or nutritional sciences A background in
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apply anyway! We offer A varied and versatile job in a motivated team that will provide you with optimal support and guidance during your induction - as well as an international working environment
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, Academy of Sciences) and international collections (e.g. David Rumsey Map Collection) Conduct semi-structured interviews with Georgian schoolteachers, textbook authors, and curriculum developers
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collaboration with partners at the Robert Koch Institute (RKI) and other Leibniz institutes. It combines bacterial cultivation, molecular biology, and microbial genomics to better understand the transmission risk
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of the authentication service (internal and external), including communication with and consulting of customers Contribute to routine tasks in the cell lines collection (characterization of cell lines) Active cooperation
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program. Requirements Very good master's degree in computer science, data science, mathematics or a related discipline; relevant research experience (e.g., master's thesis) in the field of NLP/ML/text