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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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the world, we work together to develop solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/phd-position-for-synthetic-bio
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking to hire a research fellow (postdoc) to undertake a project to develop efficient AI and Machine
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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materials using statistical mechanics, molecular simulations, and machine learning. Expectations Candidates will be responsible for: Developing multi-scale modeling methods for polymeric materials, using
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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro
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and collaborative environments. Required Education: PhD from an accredited college or university in Educational Technology, Learning Technologies, Human-Computer Interaction, or a related field
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 20 days ago
– Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities