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the group's efforts in testing, calibration, and maintenance of the detector systems installed on our scientific instruments in user operation. Your responsibilities will include ensuring their optimal
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well as application optimization. This research focuses on the development of a parallel debugging framework tailored for custom RISC-V instruc-tion set extensions. The goal is to enable efficient execution tracing
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processing - Study actin-based processes critical for health and disease using the cryo-ET workflow, from cell sample preparation and optimization to imaging and data analysis - Use computational tools for in
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods
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in solar energy by exploring fundamentally the controversy regarding the abnormal evaporation rate and simulate/ predict vapor production rate to guide the design of an optimized interfacial evaporator
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Sciences and Systems in the lab of Professor M. Bichler. We offer: - a team of young and highly motivated colleagues who are passionate about machine learning, optimization, and game theory. - strong support
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decision-making in operational settings, aiming to enhance performance and optimize decision processes. Collaboration opportunities with industry partners are available, providing a strong mix of academic
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) - Semantic 3D Scene Understanding - Face / Body Tracking, 3D Avatars - Non-Linear Optimization - Media Forensics / Fake News Detection How to Apply: Follow the instructions on our application platform: https
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods