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the Rheintal project Integrate CCUS and industrial processes into the energy system models Assess the energy system towards different metrics and optimization objectives such as cost and CO2 emissions Coordinate
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publication record in machine learning, artificial intelligence, optimization, or related areas. Excellent communication skills and fluency in English (spoken and written) are required. We also seek to increase
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may include AI/ML (incl. LLMs), XR, robotics, simulation, optimization, or others that fit your research question. We welcome foundational AI and XR proposals (e.g., representations, verification
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data manipulation techniques that exploit optimally the underlying hardware and I/O devices, and we enable new discoveries in scientific domains through automating physical database design and
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, optimization, and modernization of infrastructure and workflows Support the reliability, scalability, and security of the platform services Profile Bachelor’s or Master’s degree in Computer Science
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-specific reasoning behavior Comparison and development of RL training approaches Calibration, abstention, and safety-aware optimization Clinical Evaluation and Safety Evaluation of oncology reasoning models
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interventions with a patient’s clinical state, lesion characteristics, and multimodal biomarkers to optimize therapeutic effectiveness, across the pathway of care. This research axis is embedded in the CEREBRIS
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100%, Zurich, fixed-term We invite applications for a PhD position at the intersection of quantum computing and artificial intelligence, focused on the challenge of advancing optimization through
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-guided treatment planning and targeting Optimization of targeted drug delivery and therapeutic dosing Development of closed-loop ultrasound neuromodulation systems Design of custom hardware and software
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Boundaries. However, the current process design paradigm is too slow, labor-intensive, and fragmented between disciplines. This project will investigate optimal pathways for creating a circular industry that