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established chair Evolutionary Diversity and Biogeography. The aim of this chair is to explore the evolutionary patterns in plant-species diversity in space and (deep) time to gain insights into the origins
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scientific curiosity. You thrive at the boundary of robot learning, computer vision, deep learning, and simulation, and you are excited to see your research running on real robots. You communicate clearly
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) subsystems including deep space and near-Earth transponders, proximity and intersatellite (ISL) link equipment, high-speed downlink modulators and digital communication equipment (hereinafter referred to as
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: machine learning or deep learning (e.g. PyTorch) scientific data pipelines or large datasets knowledge graphs or structured data systems GPU or distributed computing scientific machine learning or physics
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, implementation and validation of complex ground systems delivering downstream capabilities across their full life cycle Experience of ground segment operations, in particular for Earth observation missions Deep
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. You enjoy working independently, are willing to take responsibility, and feel at home in a multidisciplinary environment. You are not afraid to dive deep into the subject matter and are eager to share
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skills: Good knowledge of ML/AI based techniques to develop fast surrogates (deep neural networks) and capability to develop own efficient model learning schemes (deep learning techniques, representation
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: Experience with one or more general-purpose programming languages, such as Python, and general-purpose deep learning frameworks. Experience with integrating multidisciplinary inputs. Demonstrated ability in
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cardiovascular applications, using integrated computational and experimental methods. The group focuses on developing a deep understanding of how mechanical stimulation regulates growth and remodeling, with
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to stay or move London School of Economics, London, UK Beth Lloyd (Leiden University) Causal contributions of (zero) prediction-error signals to learning and decision-making using transcranial ultrasound