Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Forschungszentrum Jülich
- Leibniz
- Nature Careers
- Fraunhofer-Gesellschaft
- Technical University of Munich
- University of Bonn •
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Hannover Medical School •
- Helmholtz-Zentrum Geesthacht
- Ludwig-Maximilians-Universität München •
- RWTH Aachen University
- Technische Universität München
- University of Tübingen
- University of Tübingen •
- 5 more »
- « less
-
Field
-
formation of two- and three-dimensional DNA structures which self-assemble from a number of interacting single-stranded DNA molecules. An accurate prediction of DNA structures still remains difficult, which
-
Dortmund, we invite applications for a PhD Candidate (m/f/d): Multidimensional Omics Data Analysis You will be responsible for Prediction of metabolic activity in complex microbial communities, leveraging
-
tunnel testing and statistical modelling using extreme value theory, the project will yield predictive frameworks for structural risk under rare yet damaging wind conditions. The results will support
-
Jülich who are leaders in their respective fields, viz. AI-driven materials property prediction and high-throughput materials development. Computational studies will be performed on Jülich’s world-class
-
! RESPONSIBILITIES: You will elucidate the molecular mechanisms driving the development of distinct malignant lymphoma subtypes and contribute to the identification of predictive biomarkers and novel therapeutic
-
computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
-
separately, yet a reliable, open-source tool integrating a shallow-water solver and a multiphase porous-media solver within the same framework is missing. Without this coupling, it is not possible to predict
-
of the Earth system at different temporal and spatial scales to improve predictive capability. Comprehensive education: Enjoy numerous opportunities for scientific training, skills development and problem
-
with microstructural features and failure mechanisms Development of models to describe degradation mechanisms and predict component lifetime Presentation of research findings at project meetings
-
to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer