Sort by
Refine Your Search
-
Listed
-
Employer
- Nature Careers
- Technical University of Munich
- Fraunhofer-Gesellschaft
- University of Tübingen
- Free University of Berlin
- DAAD
- Forschungszentrum Jülich
- Leibniz
- Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg
- TECHNISCHE UNIVERSITAT DRESDEN (TU DRESDEN)
- 1 more »
- « less
-
Field
-
developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
-
multi-omics data integration and the project will provide opportunities to learn, develop, and apply machine learning and deep learning methods on genomics data. Requirements: excellent university and PhD
-
Programme is a scientific visitor scheme designed to provide early-career students/researchers (prior to embarking on a PhD) with a passion for technology and tool development an opportunity to gain hands
-
a collaboration between five Helmholtz Centers (MDC, GFZ, AWI, DESY, HZB), the Berlin Institute for the Foundations of Learning and Data (BIFOLD), and three Berlin universities. To strengthen our team
-
28.05.2025, Wissenschaftliches Personal We are looking for talented and ambitious scientists interested in unique interdisciplinary research, integrating machine learning, molecular simulations
-
advanced statistical/chemometrics and machine learning tools, iv) to couple metabolome data with other omics datasets (e.g., genomics, lipidomics, metallomics, and others). Main target areas are drug
-
of research focus include machine learning/learning analytics, multimodal assessment, adaptive learning in online settings, and the role of self-regulation in learning with AI. Close networking with
-
the research area of adversarial robustness in LLMs as a Doctoral candidate / PhD Student (f/m/d) At the chair of Data Analytics and Machine Learning at the Technical University of Munich (TUM), a full position
-
macromolecular dynamics with statistical mechanics, molecular simulation at different resolutions, machine learning, and experimental data. Our group works on the definition and implementation of strategies
-
statistics, bioinformatics, machine learning and AI applications. Experience in a number of these technologies is expected. Collaborations within the Cluster of Excellence ImmunoSensation and with other intra