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The Learning Machines group seeks motivated PhD students to join our team working on learning in physical systems. What are learning machines? Imagine your favorite artificial intelligence machine
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, e.g. graphene, have gained much attention in research for their special physical properties compared to their three-dimensional counterparts. Halides or transition metal dichalcogenides in particular
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future is a thorough understanding and assessment of the thermo-physical properties (e.g melting temperature, heat capacity, density, viscosity, thermal conductivity) of the molten fuel salt during reactor
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4 Apr 2024 Job Information Organisation/Company University of Amsterdam (UvA) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application Deadline 31 May
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for applications in high-energy physics. Recently, novel 2D material devices have been developed based on heterostructures of semiconducting 2D monolayers such as transition metal dicalchogenides (TMDSs). Similar
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available validated DEM simulation models and enriched by operational equipment performance data. To this end, physics informed machine learning techniques will be used to bring model data and real data
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simulation models and enriched by operational equipment performance data. To this end, physics informed machine learning techniques will be used to bring model data and real data together in a Digital Twin
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PhD Position Physics Informed Machine Learning for Metamodeling Equipment Performance on Industrial Scale PhD Position Physics Informed Machine Learning for Metamodeling Equipment Performance
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, analyzing data, and interpreting results. Collaborate with the team to explain the root causes of model miscalibration, optimize diagnostic processes for monitoring for Cyber-Physical System diagnostics
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PhD position on Calibration in Deep Learning for Zero Downtime in Cyber-Physical Systems PhD position on Calibration in Deep Learning for Zero Downtime in Cyber-Physical Systems Published Deadline