Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
and other stakeholders - knowledge-driven and application-inspired. To strengthen theDepartment Data Science in Bioeconomywe are offering the following position to be filled on 15.06.2026: Two Student
-
Bioanalytics for the Multidimensional OMICS Data Analysis research group, we invite applications for a: PhD Candidate (m/f/d) This position is part of the Leibniz Science Campus “Cardio-Oncology Campus
-
mountains. To achieve this, we combine disciplines ranging from ecology and geography to economy and archeology, represented by large team of researchers and stakeholders from the EU and Eastern Africa
-
the design of an AI test environment for open-source Large Language Models (LLMs). Research on the influence of low-frequency expert data on LLM-based systems and development of robust strategies
-
and other stakeholders - knowledge-driven and application-inspired. To strengthen the Department Data Science in Bioeconomy, we are looking for Two Student Research Assistants (m/f/d) (40-80h per month
-
, environmental and/or ecological sciences ability to work with large environmental and ecological data sets, incl. empirical, remote-sensing and simulated model data knowledge in programming languages (UNIX, C
-
The Leibniz Institute for the Analysis of Biodiversity Change (LIB) is one of the large, globally connected research museums of the Leibniz Association. In addition to excellent research
-
insights. Second, starting from large-scale transnational infrastructures that connect peripheries to various centres reveals the complexity of political-economic integration and dependencies better than
-
will work at the interface between research, administration, and politics. Your Role: Setting up an infrastructure to categorize granular observations from large data sets Independently thinking
-
-related traits, and heterosis. In the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a