507 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD research jobs
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sciences, AI, machine learning or related fields. Strong background and track record in the development of geospatial foundation models from multi-modal Earth Observations is essential as well as strong
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of moving to a non-English-speaking country posed a challenge. I questioned my supervisor multiple times about the necessity of learning Dutch. Fortunately, she assured me that the English level is very high
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, machine learning, or data visualization tools. Long-term interest in pursuing a Ph.D. in a business-related field. Compensation and Benefits Competitive salary will be paid on a monthly basis, benchmarked
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, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates
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with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) A high motivation and the ability to work independently with a strong team orientation Excellent spoken and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
ranks as one of the nation’s top public universities . Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work
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on psychological assessment of learning and attention disorders and neuropsychological testing with youth with various medical conditions (including seizures, cancer, and kidney transplant patients). The fellows
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are encouraged to Be 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
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multiple types of sensing modalities, where this expertise is applied to solve critical national problems in energy and security. Demonstrated knowledge of emerging AI and machine learning techniques as
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: active learning (uncertain cases first), smart sampling, confidence thresholds, gradations (auto-label/review/manual), measurement and decision logic for throughput vs. quality. Proficiency in programming