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; expertise in several of the following: life cycle assessment, life-cycle cost analysis, pavement simulation, machine learning, deep reinforcement learning, and/or physics-informed modeling frameworks; and
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Do you want to combine high-throughput directed evolution with machine-learning analysis of deep sequencing data to engineer better antibodies? The Sormanni Lab in the Department of Chemical
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submitting your CV and a separate cover letter (no more than 2 pages) that demonstrates how you meet the following selection criteria: PhD in Materials Engineering, Chemical Engineering, or a related
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submitting your CV and a separate cover letter (no more than 2 pages) that demonstrates how you meet the following selection criteria: PhD in Materials Engineering, Chemical Engineering, or a related
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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Infrastructure? No Offer Description Post-doc Position (M/F) at Poznan University of Technology, Poland Project financed by National Science Centre, Poland: call SONATA 21 Project name: Deep insight into biofilm
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economy. As a postdoctoral researcher, you will unravel how silicon suppresses liquid copper infiltration at the atomic scale, using density functional theory-accurate machine-learned potentials and
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learning to understand and predict the behavior of cardiovascular tissues and organs across scales. You will work closely with PhD students, MSc students, and international VITAL partners. This is a full
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of machine learning for healthcare and related topics Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large