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Field
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integrating power electronic converters and electrical machines we can use common structures and systems to greatly reduce, material usage and energy consumption. Through a multidisciplinary research approach
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develop a new generation of hybrid models combining large-scale machine learning with physical knowledge to represent interactions between mobile robots and their environment. The research will address
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In this position, you will join our Simulation and Data Lab for AI and Machine Learning for Remote Sensing . The lab advances interdisciplinary research and operational services by combining
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compositionally complex recycled steels, using density functional theory and machine-learned interatomic potentials, in close collaboration with leading academic partners and Tata Steel. Job description At TU Delft
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is seeking a highly motivated PhD candidate to work on a fundamental research project on systems and control theory for learning in neuromorphic circuits. Neuromorphic computing is an analog, brain
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for latent variables and their connections to modern machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates
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doctoral degree Collect, structure and assess relevant sensor, operational, maintenance, incident and cost data Develop and validate statistical, causal and/or machine-learning methods and turn the results
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system integrates robotics, automated sample handling, sensor networks, imaging systems, cloud computing, and machine-learning-based analytics. The research work at NTNU will focus particularly
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with health/real grid data or machine learning is beneficial but not mandatory. We Offer One year funded of 3-year PhD position (SIF Doctoral Student Grant). Access to high-performance computing
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This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a