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. machine learning, computer science, mathematics, statistics, physics, theoretical neuroscience or a closely related field) with significant post-qualification research experience. You will experience
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoc in ML-Based Co-Design at EPFL Mission The EPFL computer vision lab (https://www.epfl.ch
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(payable 14 times per year) Responsibilities The applicant is expected to establish an own research group with focus on advanced machine learning and deep learning techniques for remote sensing applications
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Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your
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Learning: Apply shape-correspondence and machine-learning approaches, including spectral/graph-based surface alignment and autoencoder-based shape extraction, to compare limb and joint morphology across
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
. Candidates with expertise in related areas, such as lattice field theory algorithms, machine-learning methods for lattice field theory, hadron spectroscopy, or hadron-structure phenomenology, are encouraged
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, please visit: http://uhr.rutgers.edu/benefits/benefits-overview . Posting Summary Rutgers, The State University of New Jersey, is seeking a highly qualified candidate for a Postdoctoral Research Associate
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. The postdoctoral researcher(s) will join an international research environment at Umeå University, including Stat4Reg (www.stat4reg.se ), which develops statistical and machine-learning methods for register data
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– Wrocław University of Science and Technology offers employees the opportunity to teach students and participate in training programmes. International cooperation – Wrocław University of Science and
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 24 days ago
); and propagation of physics-traceable soil moisture uncertainty into precipitation estimates. Machine learning approaches are welcome as tools within this framework — for example, learning the space–time