24 machine-learning-phd positions at DAAD

  • DAAD | Germany | 25 days ago

    – from the modeling of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference

  • DAAD | Germany | about 1 month ago

    using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering

  • DAAD | Germany | 2 days ago

    the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD

  • DAAD | Germany | 2 days ago

    institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x

  • DAAD | Germany | 2 days ago

    Back to Overview Research Assistant / PhD Student (m/f/d), Machine learning chiral molecules, 75%Full PhD Working LanguageGerman, English LocationKassel Application Deadline20 Feb 2026 Starting

  • DAAD | Germany | 2 days ago

    the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data

  • DAAD | Germany | about 3 hours ago

    theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with

  • DAAD | Germany | about 3 hours ago

    Description For our location in Hamburg we are seeking: Doctoral Researcher in Machine Learning and Data Processing in the Field of Seismic Measurements Remuneration Group 13 | Limited: 3 years

  • DAAD | Germany | about 1 month ago

    the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD

  • DAAD | Germany | 20 days ago

    ), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine

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