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science foundation (DFG). Doctoral students (m/f/d) are facilitated to participate in the doctoral program in order to successfully complete their dissertation. We offer an attractive workplace with
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- Integrating exudation into the root economics space to better understand carbon and nutrient cycling in managed grasslands” is part of the DFG Priority Program 1374 “Biodiversity Exploratories”. The project
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The Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik (FBH) is an application-oriented research institute in the fields of high-frequency electronics, photonics and quantum physics. It researches and realizes electronic and optical components, modules and systems based on...
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The research group Calcium-dependent Protein Kinases at the IPB is seeking applications for the position as Research associate in AI-guided barley adaptation to rising temperatures (m/f/d) (03/2026) Salary group E13 TV-L, full-time 100 % (part-time is possible), to be filled...
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(TIB ) – Leibniz Information Centre for Science and Technology – Program Area C, Research and Development, is looking to employ a Data Engineer/ Research Data Manager (m/f/d) to work in the Open Science
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by NFDI4Biodiversity, part of NFDI, the German National Research Data Infrastructure Program. The project position is part of our Senckenberg Data and Modelling Center (SDMC) with experts in the areas
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researchers specializing in marine segmented worms (Annelida) with comparative genomics experts. Its goal is to better understand European biodiversity using cutting-edge molecular and computational techniques
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program. Requirements Very good master's degree in computer science, data science, mathematics or a related discipline; relevant research experience (e.g., master's thesis) in the field of NLP/ML/text
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transport Easy accessibility by public transport or car (including free parking) 30 days of vacation Participation in the benefits program for employees („Corporate Benefits“) The advertised position is
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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