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preferably start around 01-12-2025 and requires knowledge of geometric image processing and machine learning. Information As Post-doctoral Researcher within VICI Project "Geometric Learning for Image Analysis
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emerging spectrum (FR3, MMW, sub-THz/THz) Extreme massive MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless
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, artificial intelligence, machine learning, cybernetics or a closely related technical field. Competence in implementation and evaluation of AI systems. Expertise in distributed AI systems, autonomous multi
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] Subject Areas: Physics / Hard Condensed Matter Theory , Machine Learning , Material Science , Physics , Quantum Information Science , Soft Condensed Matter Theory , theoretical condensed matter physics
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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machine learning and statistics; experience with Gaussian process regression and/or probabilistic regression. Experience with normative modelling is an advantage. Proficiency in Python (and ideally C/C
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simulations), computational chemistry, machine learning, enhanced sampling methods, force field development, or related fields are encouraged to apply. Start date is flexible. the postdoc will collaborate with
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, machine learning & data mining (#65), software engineering (#71), mobile computing (#18), and computer security (#88). In the last few years, students and faculty in the department have received
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experience in machine learning and image analysis for ultrasound images and video. The successful applicant will possess specialist experience conducting fieldwork, particularly in low-resource or rural
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profile: A PhD in AI, preferably at the interface of information retrieval and machine learning; Research background in generative information retrieval, with publications in the leading venues relevant