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Field
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), 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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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
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Develop new machine learning
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machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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Job related to staff position within a Research Infrastructure? No Offer Description PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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research environment for biophysics. Our group combines molecular dynamics simulations with machine learning techniques to understand how proteins, biomembranes, and small drug-like molecules interact
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data