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to qualification programs and further training opportunities Remuneration according to the collective agreement of the federal states (TV-L) up to E 13 (including annual special payment) Company ticket A collegial
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-on experience in programming for data analysis is an advantage. Proficiency in English is required; German is helpful but not essential. We Offer A 3-year E13 TV-L 60% contract with the possibility of increment
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admission to municipal museums – annual special payment – collectively agreed vacation entitlement – company pension plan (ZVK) Senckenberg is committed to diversity. We benefit from the different expertise
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of standard MS programs and a good command of written and spoken English. What we offer Employment in accordance with the collective agreement for the public service of the federal states (TV-L) A modern, well
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other relevant fields. You have programming experience in Python and/or R (e.g. scikit-learn, PyTorch, TensorFlow). You have knowledge of omics technologies, ideally mass spectrometry and chemometrics
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%, limited for 3 years, start: as soon as possible) in the trilateral program “Future Proofing Plants to a Changing Climate” (funded by DFG, UKRI-BBSRC, NSF, USDA-NIFA) Who we are: The research group Symbiosis
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to develop long term, quantitative strategic plans that emphasize sustainable agribusiness enhancement. This PhD position is carried out in collaboration with the Doctoral Program in Agricultural and Forestry
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. The successful candidate will receive careful mentorship both from the supervisor and from other peers through a dedicated mentorship program. Technical queries should be directed to Benedikt Jahnel
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Leibniz Association. The following position is available at the Institute subject to approval by the funding organization from October 1, 2025, for a fixed term of three years, in the program area "Next
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to research this topic. Interest in laboratory work and basic technical understanding. Fluent written and spoken English. Programming skills in e.g. Python, R, Matlab and Java. Experience in image processing