176 computer-programmer-"https:"-"Inserm" "https:" "https:" "https:" "https:" "https:" "https:" "P" positions at Leibniz in Germany
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. At our location in
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
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contact details of referees via our online application portal for this job posting (reference number 2026-TA-1) at https://www.atb-potsdam.de/en/career/vacancies . Applications received after
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The LIT - Leibniz Institute for Immunotherapy (foundation under civil law) (https://lit.eu/ ) formerly RCI – is a biomedical research center focusing on translational immunology in the fields
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our online application portal for this job posting, reference number 2026-SY-1, at https://www.atb-potsdam.de/en/career/vacancies . Applications received after the application deadline cannot be
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by the University of Hamburg. All further information on the application process and contacts can be found here: https://www.uni-hamburg.de/en/stellenangebote/ausschreibung.html?jobID
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, annual bonus, company pension plan with the Versorgungsanstalt des Bundes und der Länder (VBL). In-house support for Fellowship applications. Work-life balance (certified by Audit Beruf und Familie) as
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opportunities in research methods and academic publishing. Doctoral candidates at the GWZO participate in the program of the Integrated Research Training Group of the Graduate School Global and Area Studies
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instruction and guidance Flexible working hours and the possibility of mobile working (at least 20% of the weekly working hours agreed in the contract) We promote a good work-life balance Comprehensive program
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in