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requires good theoretical and hands-on expertise. Perfectly suited for those at the intersection of theory and application. Develop customized ILC and parameter optimization algorithms for industrial
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complements our existing scientific software team by bringing dedicated expertise in power plant engineering, process technology, thermal-fluid system design, and techno-economic optimization. Job
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will contribute to the development and optimization of next-generation fabrication technologies with direct relevance to advanced X-ray imaging applications. The SNSF-funded project ABSOLUTE (n A
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data transparency and multi-stakeholder collaboration across phases to improve decisions. Methods may include AI/ML (incl. LLMs), XR, robotics, simulation, optimization, or others that fit your
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, process design, energy system optimization, and life cycle assessment, working collaboratively with research and industry partners. You will work in an inspiring, collaborative environment to address
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Fabrication: simulation, optimization, and learned surrogate models to design and fabricate efficient, bioinspired robots. Reinforcement Learning and Machine Learning: data-driven methods that let robots learn
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oncology-specific reasoning behavior Comparison and development of RL training approaches Calibration, abstention, and safety-aware optimization Clinical Evaluation and Safety Evaluation of oncology
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interests, the project may include: Development of next-generation focused ultrasound systems fMRI-guided treatment planning and targeting Optimization of targeted drug delivery and therapeutic dosing
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., microbubbles, nanodroplets, liposomes, or polymeric/lipid nanoparticles) Optimization of drug loading, encapsulation efficiency, and release kinetics Physicochemical characterization of carriers (size, zeta
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hidden in conventional measurements. The resulting understanding will guide the synthesis and optimization of semiconductor nanocrystals for applications requiring highly uniform optical properties