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Leibniz-Institut für Astrophysik Potsdam (AIP) | about 2 months ago
duration be extended? No Work Arrangement In-Person In-Person Location(s) Potsdam Germany Job Description We invite applications for doctoral student positions in Computational Astrophysics for
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computational, experimental, observational, and theoretical approaches. Existing research programs at KIPAC span many areas of astrophysics and cosmology and include studies of dark energy and cosmic dynamics
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, associated with the Q Ontic Initiative—an interdisciplinary project at the interface of quantum foundations, computational physics, and physics education. The position focuses on the development of
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scientists who use theoretical, computational, and/or observational approaches to study any aspect of the “Extreme Universe”, including multi-messenger/time-domain Astronomy and high-energy/plasma
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aperture DKIST). There is also the option to develop numerical simulations of the spicule processes by means of our market-leading computational tools, would that be a preferred methodology of the student
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theoretical level. There may be scope to implement aspects in the ideas you develop into AI systems or mathematical and computational models of brain function. This project would be for someone who wishes to
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theoretical level. There may be scope to implement aspects in the ideas you develop into AI systems or mathematical and computational models of brain function. This project would be for someone who wishes to
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our department as the science themes themselves - computational astrophysics, instrument development, and a multi-messenger approach to exploring and studying the Universe. Members of the department
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, please see: https://sensilab.monash.edu/work-with-us/practice-based-phd/ Required knowledge Experience or an interest in art (particularly drawing) and a background in AI or Mechatronics. URLs and
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temporary work-study position for eligible students with FWS funding, supporting administrative and technical operations related to human subjects research with a strong emphasis on computational data