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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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states, charge density waves, superconductivity, and quantum magnetism - Kagome materials and superconducting hydrides - Machine learning interatomic potentials (MLIPs) and data-driven atomistic
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mechanical loading of such samples. The focus of the PhD project will be to use machine learning techniques to better understand the interplay between the crystal orientations and deformation patterns in a
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machine learning. There are currently 54 academic staff and about 105 research personnel in the Department. Please visit the website at https://www.polyu.edu.hk/ama for more information about the
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Degree Doctor of Philosophy (PhD) / Doctor rerum naturalium (Dr rer nat) Course location Hannover In cooperation with Twincore - Centre for Experimental and Clinical Infection Research, University
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learning, discovery and personal growth. The University is accredited by the Southern Association of Colleges and Schools and has earned special accreditation from professional and academic associations
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foods including through high moisture extrusion. Key responsibilities will include: Explore innovative methods for food process optimization including the use of AI and machine-learning Develop and
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accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform performance, power, and area
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in
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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a