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with SCION in New Zealand bringing together researchers in robotic perception, machine learning, remote sensing and silviculture to transform and upscale forest phenotyping operations. The role will be
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environment and governance will be highly desirable. Experience in computational social science, causal inference, text mining, machine learning, analysis of unstructured and multimodal data, or advanced
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contributed to the identification of vaccine and therapeutic candidates currently being produced in Good Manufacturing Practice facilities for early phase clinical trials. Minimum Requirements: PhD in
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contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and
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experience in machine learning and image analysis for ultrasound images and video. The successful applicant will possess specialist experience conducting fieldwork, particularly in low-resource or rural
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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: Quantum Computing / Quantum Computing High Energy Physics / accelerator , astrophysics , BSM , CMS , cosmology , Dark Matter , Experiment , Flavor Physics , Higgs physics , Lattice QCD , LHC , Machine
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and analysis Gaussian processes, random functions, rare events, harmonic analysis Shira Faigenbaum-Golovin Manifold learning, shape space analysis, machine learning, mathematics of data
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simulations), computational chemistry, machine learning, enhanced sampling methods, force field development, or related fields are encouraged to apply. Start date is flexible. the postdoc will collaborate with
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for the Research Associate, Grade 7 level, position must have a PhD in a quantitative biology discipline, statistics or machine learning along with a proven track record of research using statistical modelling