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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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advanced vehicle concepts and better control systems. Actively changing the geometry of the aerodynamic lifting and control surfaces, enables reconfiguration of vehicle structure in real-time to optimized
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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; proficiency in graph data structures and algorithms for geometric analysis; advanced knowledge of surface representation math; experience in writing geometry translators for complex surface features; excellent
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research at the interface between geometry, mechanics, materials science, computation, and control theory. PhD positions Applicants for PhD positions are expected to have a strong background in mathematics
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of Mathematics at Cornell. Members of the lab engage in interdisciplinary research, drawing on approaches from geometry, topology, graphs and networks, probability/statistics, and algorithm design, in conversation
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, and various geometry models (Computer Aided Design, unstructured mesh, Constructive Solid Geometry, etc.). Familiarity with established nuclear systems analysis software (such as SCALE, Nuclear Energy
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of aviation and aerospace, and other STEM-related disciplines. Embry-Riddle offers programs in seven primary fields of study including: Applied Science; Aviation; Business; Computers and Technology; Engineering
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analysis of nuclear cardiology data using novel algorithms and machine learning techniques, and on the development of integrated motion-corrected analysis of positron emission tomography (PET)/computed
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., biomarkers, metabolites) must be evaluated using digital twins of breath device prototypes. Our digital twins are based on simulations using computational fluid dynamics (CFD) and computational fluid and