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complex geometries arisen from emerging applications. The hire is in line with a University wide initiative to advance the application of Computational Science in interdisciplinary research. Key
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for faculty positions in mathematics and related interdisciplinary areas, including but not limited to: Computational and applied mathematics; artificial intelligence for sciences (especially biomedical science
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focuses on mechanical and morphological evolution of the insect heart, as part of the recently funded Human Frontier Science Program (HFSP) grant awarded to Prof. Young’s lab. The heart is one of the first
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REQUIREMENTS The Department of Computer Science and Engineering is seeking part-time Research Assistant/Programmer to assist with robotics and machine learning research as well as data collection and data
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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for program success and provides sound technical solutions for complex problems and establish novel test controls drawing upon personal experience; works closely with OSU faculty, MAE staff and students
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support the Plutonium-238 Supply Program at ORNL that is responsible for producing plutonium-238 for NASA in support of powering deep space missions. Major Duties/Rsponsibilities: Perform experimental and
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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Understanding of and ability to contribute to broader management/administration processes Contribute to the planning and organising of the research programme and/or specific research project Co-ordinate own work
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Kahl (Computer Vision, Chalmers), Kathlén Kohn (Algebraic Geometry, KTH), and Mårten Björkman (Robotics, Perception and Learning, KTH). The research focuses on developing novel machine learning methods