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the ocean. The researcher must have knowledge of atmospheric science as well as a proven record in scientific applications of machine learning. The postdoc will participate in co-mentoring at least one junior
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work to discover cell specific isoforms and relate them to pathological signatures and genetic risk factors in ALS patient tissue. You will apply supervised and unsupervised machine learning methods
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polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
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about the lab and their work can be found by visiting https://sarvestanilab.com/ About the Postdoctoral Scientist role: We are seeking a motivated and creative Postdoctoral Scientist to join our dynamic
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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responsibilities (10%): · Supervising and mentoring research staff, PhD students, or postdocs · Providing guidance, training, and technical support to others in the research team · Ensuring
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by the European Research Council - ERC COG 101088763. The work for this position is in the area of Machine Learning, Decision Theory, Reinforcement Learning. Scientific Area: Information and Data
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 2 months ago
seek candidates with strong skills in programming (e.g. R or Python), statistics, machine learning, and data science. A good publication record with respect to your career stage and research interests in
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weak gravitational lensing, galaxy clusters, or large-scale structure. Experience with cosmological simulations and machine learning is highly desirable. Postdoctoral associate in exoplanet atmospheres
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Railway Engineering is seeking a motivated and collaborative postdoctoral researcher for a project on developing machine learning tools for pavement management. The project is conducted in collaboration