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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
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applications for a PhD Student or Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and
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AI systems are reshaping how we learn, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s
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candidate will play a key role in designing and implementing innovative solutions at the intersection of sensor data collection, machine learning, and real-time decision-making. Specifically, the candidate
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with e-CALLISTO instruments or Software-Defined Radios (SDRs). · Familiarity with machine learning for astrophysical data analysis. · Knowledge of solar radio data pipelines and event classification
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, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s mission is to establish an internationally
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courses on advanced semiconductor technologies Design pathfinding PDKs as learning assets Interuniversity research programs across Europe 🔬 Nano IC-related PhD topics include: Machine-learning for epitaxy
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experimental design. Collaborate with another postdoc in the NIH Center to use scientific machine learning (SciML) to automatically select mathematical models from data. Minimum Requirements: Ph.D. in applied
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motivated to do PhD research in mathematical machine learning, with special emphasis on mathematical foundations for explainable AI? If yes, the Korteweg-de Vries Institute for Mathematics at the University
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, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s mission is to establish an internationally