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We are currently inviting applications for a Postdoctoral Research Associate in Deep Learning to work with Professor Justin Sirignano at the Mathematical Institute, University of Oxford. This is a 6
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start date. Preferred Qualifications: Research experience in computer vision, NLP, geospatial data systems, or high-performance computing. Brief Description of Duties: The Postdoctoral Associate will
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performance utilizing a variety of tools including life-cycle assessment (LCA), machine learning techniques, and/or optimization methods. This position will carry out state of the art research into the economic
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the computational task: first-principles active-site descriptor models, high-throughput screening with machine-learned interatomic potentials, and a dedicated catalysis database. This position is ideal for a
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leading experts in autism research, computer vision, machine learning, psychiatry, and developmental science to develop innovative technologies that improve how caregiver-child interactions and
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the department and the funding agencies. The successful candidate will join the Machine Learning & Data Science research group and conduct research on the mathematical theory of deep learning as part of the joint
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. For example, investigating costs and benefits related to the adoption of state-of-the-art technologies that permit tracking and chain of custody. The team will also explore machine learning and artificial
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Bayesian inference, likelihood-free inference, uncertainty quantification, identifiability analysis, or scientific machine learning. Strong programming skills (Python, Julia, Matlab, C++, or similar). Strong
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and