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Field
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Job Reference: 1168098 About the Role: You will play a key role in advancing distributed and adaptive AI methods, focusing on scalable software frameworks, learning algorithms, and orchestration
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Climate Plan. You will research, use and build on existing methods to take data about the subsurface (seismic surveys, borehole data, geological mapping and other data) and produce estimates of the physical
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Number U250093 Posting Link https://www.ubjobs.buffalo.edu/postings/59894 Employer University Affiliates Appointment Term Position Type Posting Detail Information Position Summary This is a NIH, NLM T15
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at the Department of Informatics. Position as Postdoctoral Research Fellow available at the Department for Informatics with the research group Digital Signal Processing and Image Analysis (https://www.mn.uio.no/ifi
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Area: Computer Science 2. Admission Requirements: Graduates (Licenciatura) in computer engineering or related area, with experience in Machine Learning/Deep Learning methods/techniques. 3. Project
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estimate atmospheric trace gas source-receptor relationships, or measurement “footprints”, orders of magnitude more quickly than traditional 3D simulators (https://doi.org/10.5194/egusphere-2025-2392). We
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) on physical robots. • Use evolutionary algorithms to optimize both the robot’s body and brain together. • Apply quality-diversity methods to discover a wide range of high-performing designs
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that can estimate atmospheric trace gas source-receptor relationships, or measurement “footprints”, orders of magnitude more quickly than traditional 3D simulators (https://doi.org/10.5194/egusphere-2025
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee Artificial Intelligence (AI) related fields
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preferably be familiar with the Pandas, Scikit-learn, Pytorch and Flask packages. Ability to creatively apply relevant research approaches, models, techniques and methods, especially in the area of machine