166 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Leibniz in Germany
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between biodiversity and climate change. The postdoctoral position is embedded in the the collaborative project Past to Future: towards fully paleo-informed future climate projections (P2F; https
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with the research groups at the DPZ and the Göttingen Campus. PhD projects cover a broad range of topics. A structured PhD program will offer many opportunities for the development of scientific and
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January 2026 to (see button e-mail application below). https://jobs.zalf.de/jobposting/af3d771faf0a6dcc04a638f8f0d8f039bd501f6f0 If you have any questions, please do not hesitate to contact us: Dr. Ehsan
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the Editorial Board of the scientific journal Soil Organisms Participation in academic teaching at the MSc level programs of Dresden University of Technology Your Profile Doctoral degree in zoology or a related
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funding programme therefore invites young scientists in Southeast Asia to submit project applications for field and/or laboratory research, in particular for explorations and excavations of new fossil sites
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cooperation with ZPID‘s infrastructure departments. In presence teaching in the psychology B.Sc. or M.Sc. program with a reduced teaching load compared to regular junior professorships. Interdisciplinary focus
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quantitative skills and programming skills in R Experience with field work in remote and/or tropical areas Ability to work under physically demanding conditions Strong interest in the analyses of ecological
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English-language skills. Experience with programming is highly recommended. Above-average interest in the topic, we consider self-motivation and the ability to face new professional challenges as self-evident
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– company pension plan Senckenberg is committed to diversity. We benefit from the various expertise, perspectives and personalities of our staff members and welcome every application from qualified candidates
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programming skills (Python; ideally with experience in databases and cloud environments). Experience in image analysis and computer vision, ideally in the context of biological samples or materials science