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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a PhD student: New Deep Learning - based Framework for Energy Modelling: Combination
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aim to leverage high-throughput phenotyping to create knowledge about plant function at the physiological level and use forward genetics approaches to unravel the genetic architecture of root traits
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Knowledge of renewable electricity systems and/or a background in atmospheric sciences is an advantage Experience in atmospheric/climate modeling, renewable electricity generation simulation and/or energy
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of the continent with the requisite knowledge, skills and attitudes. The specific objectives of the PhD programme are to: Produce researchers and educators in the above-mentioned interrelated areas of regional and
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artificial intelligence, biology, (cognitive) neuroscience, genetics, linguistics, mathematics, neurobiology, neuroimaging, neurology, neurophysics, philosophy, physics, psychiatry, and psychology
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biogeochemistry, environmental sciences, or a related field is required. Knowledge of the biogeochemistry of trace gases such as methane in shallow water areas would be advantageous. Existing skills in measuring
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engineering Willingness to work in laboratory and cleanroom environments Ideally, initial experience in a technical or scientific environment (e.g. cleanroom, laboratory) Knowledge of solid state physics and/or
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Weihenstephan-Triesdorf University of Applied Sciences (HSWT). As part of an applied research collaboration, a PhD position is available at the high-tech startup lifespin GmbH in Regensburg. The doctoral degree
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, France; Coventry, UK; and Lviv, Ukraine). Academic admission requirements Typically, a Master's or "Diplom" degree in natural sciences Language requirements Knowledge of English Basic knowledge of German
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Participation in the development of the institute Your Profile: Sucessfully completed scientific university degree (Master) in the fields of technical chemistry, physical chemistry or a comparable discipline