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course Internal Number: 177445 The Department of Pediatrics at the University of Chicago seeks part-time lecturers to develop and teach courses in the Master of Science in Biomedical Informatics (https
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analytics (chromatography, Raman spectroscopy, Surface Plasmon Resonance, etc.) Data analysis Machine learning Additional Information Work Location(s) Number of offers available1Company/InstituteUniversité
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in autonomous systems such as ground and aerial vehicles, and mobile robots. This includes: formulating and solving long-standing multiterminal information theory problems using modern machine learning
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Advanced brain-computer interface School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year round
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of Vienna). About the position: Lead the research group focusing on hybrid quantum algorithms, quantum neuromorphic computing, and quantum machine learning Build your own team (PhD students, postdocs) 4-year
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who could help with general course delivery, project supervision and marking of assessments. The post holder will teach undergraduate and computing modules within the School of Computing and Engineering
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three decades, the Department of Physics has been offering graduate programs with MS and PhD degrees in Physics with emphasis on Nuclear and Optical Physics. A new emphasis is being added on Plasma
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applications for faculty positions in Computer Science. Faculty specialising in data science, machine learning (deep learning, reinforcement learning, multimodal learning), Generative AI, and computer graphics
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action recognition, and enable seamless collaboration between humans and machines. Long-Term Human-Technology Evolution: investigate the longitudinal impact of human-technology interaction on learning
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Ecole Nationale des Ponts et Chaussées (ENPC) | Champs sur Marne, le de France | France | about 1 month ago
-scale (~10’s of km2) permafrost thermo-hydrological hybrid twin, to be coupled with state-of-the-art freezing/thawing soil mechanics machine learning-based surrogate models (Richa et al., 2024, Tristani