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collisions and maximize efficiency through innovative AI-based movement and maneuver planning. For the first time, innovative machine learning concepts, such as “shadow learning”, are being used. Appropriate
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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the formula 0,40PQ + 0,40PV + 0,20AI. PQ corresponds to the quantitative evaluation of publications in ISI/SCOPUS journals: in advanced statistical models (e.g., Machine Learning), as well as in programming
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, machine learning or causal inference for estimating, understanding and forecasting demographic and health outcomes, at the individual and aggregate levels, including as they relate to life course and socio
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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-to-system solutions to prepare and submit your application to Grants.gov and track your application in eRA Commons. Learn more . Table of Contents Part 1. Overview Information Part 2. Full Text
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of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k
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, or machine learning is also appreciated. PhD: The candidate is expected to have some background in theoretical computer science, including some of the following areas: automata, logic, games, verification