988 machine-learning-"https:"-"https:"-"https:"-"Simons-Foundation" Fellowship positions
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: Masters/Ph.D. degree in Electrical/Computer Engineering, specialized in Power Systems/Renewable Energy Planning/Optimization At least 5 years of professional experience with a strong focus on power system
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of design and fabrication of medical devices, 3D printing, microfluidics, mechanics of materials, biomaterials, blood-material interactions, computer aided design, and/or in vitro/in vivo evaluation
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years of post-qualification experience at the time of application; (b) experience in using machine learning for research projects; and (c) have a good command of both written and spoken English
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, such as, geometric/topological/algebraic data analysis, geometric/topological deep learning, Math for AI, categorical deep learning, sheaf neural networks, PINN/KAN models, neural operators, etc, and
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Computer Science, AI/ML, Computational Biology, Food Science with computational expertise, or a related field. Experience with natural language processing, machine learning frameworks (e.g., PyTorch
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for real-time surveillance and precision applications. Learning Objectives: The candidate will gain hands-on experience and advanced knowledge in utilizing cutting-edge geospatial tools, including UAV-based
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invaluable hands-on experience and develop advanced skills while working closely with the Research Entomologist throughout all phases of the research process. This opportunity will allow you to learn and
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest in creative or artistic applications. Documentary evidence would be beneficial
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to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning, AI, and other algorithmic techniques in qualitative
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nowcasting platform that delivers real-time, hyperlocal information on urban heat risks in tropical cities. Leveraging Doppler lidar–based microclimate studies and machine learning, the research emphasizes