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with excellent English proficiency to explore this fascinating intersection of experimental physics, machine learning, and complex systems. A background in optical microscopy and machine learning is of
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strong background in the physical sciences who are intensely interested in biosciences. Physicists, biophysicists, and polymer scientists, as well as physical chemists with a strong computational
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image
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comparable) in physics; interest in basic and application-related research; high self-motivation; experimental skills in optics and material preparation; familiarity with the broader field of low-dimensional
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years. In total there will be about 25 doctoral researchers who will conduct soft matter research combining fields as diverse as physical chemistry, spectroscopy, synthetic organic and polymeric synthesis
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Successful candidates have strong skills in computational molecular (bio)physics, structural biology and scientific computing, as well as a keen interest in interdisciplinary research and
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candidate will investigate ion transport through atomically thin membranes made of 2D polymers and graphene derivatives in close collaboration with experimental partner groups MPI Halle and Leiden University
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Materials and Devices – Structure and Function of Materials (IMD-1) to establish a data-driven, experimentally grounded workflow for rapid microstructure-property optimization in steels. The PhD student will
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experimentation (IMD-3: Institute of Energy Materials and Devices – Photovoltaics) and high-performance computation (IET-3: Institute of Energy Technologies – Theory and Computation) towards the overarching aim
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Financing yes Type of Position Full PhD Working Language English Required Degree Master Areas of study Physics, Experimental Physics Description Description For our BMBF-funded research project