Sort by
Refine Your Search
-
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) Flexible
-
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) Flexible
-
plan (VBL) Flexible, family-friendly working conditions Good transportation connection with parking facilities Restaurants and cafeterias in close proximity Central location near the city center You can
-
the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association www.leibniz-gemeinschaft.de . You can find more details on the institute webpage: www.ikz-berlin.de . The Section Fundamental
-
funded by the Leibniz Collaborative Excellence program and conducted in cooperation with the Institute of Space Systems at the University of Stuttgart. The position includes setting up a multi-metal lidar
-
standards in biodiversity text analysis Disseminate research results through peer-reviewed publications, academic conferences, and collaborative research proposals Your Profile MSc in biodiversity informatics
-
%, 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
-
. The communication language of the lab is English. The group interacts tightly with the Research Group Cognitive Neurophysiology (PI M. Yoshida; in-vitro/in vivo electrophysiology & computational neurosciences) as
-
simulations Enhanced sampling Molecular Dynamics simulations Your Profile The ideal applicant has a strong background in bioinformatics or computational chemistry, as well as data analysis and solid
-
Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the