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. As part of a multidisciplinary team of academic and industrial researchers, you will contribute to the development and optimization of next-generation fabrication technologies with direct relevance
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cutting-edge research in the fields of matter and materials, energy and environment and human health. By performing fundamental and applied research, we work on sustainable solutions for major challenges
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the ability to harness and optimize massive computational resources. However, this rapid growth in computational demands comes with a critical challenge: energy limitations. Around the globe, new power plants
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develop novel learning-based control and policy optimization techniques. We're looking for a skilled machine learning (ML) engineer to develop cutting-edge AI algorithms for digital twin applications in
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solutions, not just infrastructure — someone who sees a research challenge and immediately starts thinking about what combination of agents, models, and pipelines could solve it. Part of the work is carried
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Our research group focuses on the development of AI algorithms for industrial applications. The main scope of our activities is the optimization and automation of workflows and production systems
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) show how your work creates impact to improve resource efficiency, reduce carbon emissions, or increase productivity. Some example research areas include, but are not limited to: AI-Enhanced Design
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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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application. Develop customized ILC and parameter optimization algorithms for industrial applications, going from theoretical analysis to implementation and testing on real systems Develop adaptive control and
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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