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Field
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studies for the following degree programmes: Physics and/or Applied Computer Studies and/or Computer Studies or related degree programmes, ability to teach classes using the tools for distance learning
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sustainable operation of future energy networks by combining our knowledge of energy systems with cutting-edge developments in machine learning, generative AI, and digital infrastructures. Your Job
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
world. Position Summary The postdoctoral researcher will conduct advanced research in artificial intelligence (AI) and machine learning, with a focus on developing novel algorithms and systems. The position offers
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to the successful execution of R&D projects. Responsibilities include providing technical contributions as a software engineer for a wide range of projects involving machine learning (ML) and artificial intelligence
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range of projects involving machine learning (ML) and artificial intelligence (AI), including autonomy, sensing and communication, and decision support systems, among others. The R&D Engineer will work
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to the successful execution of R&D projects. Responsibilities include providing technical contributions as a software engineer for a wide range of projects involving machine learning (ML) and artificial intelligence
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and Machine Learning. The selected candidates will have the opportunity to contribute to cutting-edge research and innovation projects including the Pharos-CY project. The Pharos-CY project aims
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simulation - Scientific software development in C/C++, Fortran, and Python. - HPC/GPU computing - GIS, remote sensing, and geospatial analysis - Machine learning and deep learning Department Information
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difference at the intersection of cutting-edge technology, world-class education, noble purpose, and timeless legacy? As a Machine Learning and Generative AI Engineer on our team, you will help lead the
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: Probabilistic generative models (VLMs, diffusion, flow models) Reinforcement learning & Markov decision processes Causal inference & counterfactual reasoning Mechanistic & physics-informed modeling Agentic AI