175 computer-programmer-"https:"-"FEMTO-ST" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Leibniz
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Individual development plans, mentoring programs, and support from experienced specialists Open, team-oriented work atmosphere in an international environment 30 days of annual leave Company pension plan (VBL
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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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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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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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genomics will be used to address questions relating to evolutionary relationships and biomineralization in Annelida. This position is funded through the Leibniz Collaborative Excellence Programme, with
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of family and career Excellent conditions for developing a scientific career, including: in-depth knowledge in the fields of liver research and toxicology (Examples of our publications: https://doi.org
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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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preference. Your application: We are looking forward to receiving your online-application (http://www.ipk-gatersleben.de/en/job-offers/) as one single pdf-file by 15.02.2026. If you have questions or require
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), the largest long-term educational study in Germany. Your work environment ENTAILab is the core infrastructural service and research centre of the “New Data Spaces” program, a DFG-funded multi-local
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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