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, storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into practical tools for sustainable urban energy systems, supporting applications in forecasting
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solutions that enhance ecological monitoring, improve resilience planning, and promote sustainable resource management. Development of a Detection Transformer through Attentive Deep Learning and Explainable
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | about 2 hours ago
well as experience in omics data analysis, and possesses solid English-language skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX
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join a team of advocates who co-teach the clinic and supervise clinic advocacy partnerships around the world. The clinic works to advance human rights and address global power imbalances while training
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skills: Good knowledge of ML/AI based techniques to develop fast surrogates (deep neural networks) and capability to develop own efficient model learning schemes (deep learning techniques, representation
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be focused on deep learning based dose accumulation for pancreas patients undergoing MR-guided radiotherapy under the direction of Drs. Neelam Tyagi and Harini Veeraraghavan in collaboration with a
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of deep neural networks in the field of adaptive processing of graph data (Deep Graph Learning) . The developed novel approaches will be applied to case studies in bioinformatics Requirements Additional
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into actionable insights, novel tools, and impactful research outcomes. Key Responsibilities Develop, implement, and optimise AI/ML models (artificial intelligence/classical machine learning, deep learning
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Location Lexington, KY Grade Level 44 Salary Range $43,805-70,075/year Type of Position Staff Position Time Status Full-Time Required Education MA Click here for more information about equivalencies: https
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the world’s largest supercomputers (Polaris, Aurora) and some of the most advanced characterization tools in the world at Argonne and Sandia National Labs. Candidates with a background in deep learning