Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
(at)tum.de . More information on the working group can be found here: https://www.leibniz-lsb.de/en/research/research-sections/section-i . Please send your application, including a tabular CV, motivation
-
upload your CV and motivation letter, by February 15th , 2026 via the online application system: https://www.leibniz-inm.de/en/job-offers-2/ For further information on this position, please contact INM
-
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
-
The LIT - Leibniz Institute for Immunotherapy (foundation under civil law) (https://lit.eu ) – is a biomedical research center focusing on translational immunology in the fields of cancer
-
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
-
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
-
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
-
– 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
-
increasing sustainable economic prosperity and social participation under constantly changing conditions. Want to know more about us and your career opportunities? Come and meet us at https://www.ifo.de/en
-
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