Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
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
-
for the honeybee research program. Postdoctoral Researcher (f/m/d) “Insect Systems Neuroscience - Sleep, Social Reward and Memory Consolidation in Honeybees” The Post-Doc position, with a salary of TV-L E13 in full
-
system: https://www.leibniz-inm.de/en/job-offers-2/ For further information on this position, please contact INM Scientific Director Prof. Dr. Aránzazu del Campo (aranzazu.delcampo(at)leibniz-inm.de
-
Student or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d)
of processing steps and results Your qualifications: Ongoing B.Sc. or M.Sc. studies in geosciences, environmental sciences, geography, agricultural sciences, computer science, or a related field at a German
-
for mobile working Modern equipped offices, social rooms, company health promotion, parent-child room, etc. for a pleasant working environment (details on our social benefits at https://www.lifbi.de/Career
-
Gesellschaft für Naturforschung Senckenberganlage 25 60325 Frankfurt a.M. E-Mail: recruiting(at)senckenberg.de If you have any specific questions about the position, please contact Prof. Dr. Thomas Hickler
-
Frankfurt a.M. E-Mail: recruiting(at)senckenberg.de If you have any specific questions about the position, please contact Prof. Dr. Julia Sigwart at julia.sigwart(at)senckenberg.de . For data protection
-
is successful. For further information, please visit the website: https://www.kmk.org/zab/central-office-for-foreign-education.html For further information or to discuss the position please contact Dr
-
-Mail: recruiting(at)senckenberg.de If you have any specific questions about the position, please contact Prof. Dr. Andreas Mulch at andreas.mulch(at)senckenberg.de For data protection information
-
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