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landscape constrains or enables discovery. The project draws on tools from topological data analysis (e.g., persistent homology, Euler characteristic curves, discrete curvature), machine learning (e.g
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of computational methods that enable machines to perform tasks requiring perception, learning, reasoning, and decision-making. It encompasses core areas such as machine learning, data-driven modeling, intelligent
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to teach in at least one of the thematic areas listed above. Additional desired qualifications include a PhD degree, the ability to teach across multiple areas of the curriculum, strong engagement with
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instructor to teach a total of six courses over the course of one year. In Summer 2026, the instructor will be responsible for teaching LA 7005, LA Design Studio NYC, and LA 7006, LA Design Seminar NYC, both
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to eligible team members. Learn more at https://hr.duke.edu/benefits/ Minimum Qualifications Education See job description for education requirements. Experience See job description for requirements. Degrees
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Advanced brain-computer interface School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year round
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Job description: DESY The CMS Quantum Computing group develops generative machine learning models for detector simulations, specifically the simulation of showers in calorimeters: Proof-of-principle
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, technical depth, and a strong track record of applied research in Computational Biology, Structural Biology, Protein Engineering, Machine Learning, or a closely related field. Strong understanding and
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for a dedicated PhD student to join our team. Find more information about the Strategic Management area and its members here: http://strategy.univie.ac.at What you will be doing: In
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candidate will hold a PhD in geosciences, applied machine learning, data assimilation, or applied mathematics. The selection will be based on the following scientific and technical criteria: Experience in