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2 — additional desirable expertise: reinforcement learning, imitation learning, optimal control, dynamical systems, or related ML areas; experience with physics simulators (MuJoCo). Familiarity with
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nanozymes, and optimize their physicochemical and catalytic properties. Develop functional implant coatings: Establish reproducible strategies for integrating nanozymes onto implant surfaces and investigate
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infrastructure to support you in optimizing your schedule to accommodate your personal interests and family commitments. chevron_right Working, teaching and research at ETH Zurich We value diversity and
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modulation, wave propagation, and temporal scattering Design and optimize subwavelength THz waveguides that enable homogeneous optical switching and efficient time interfaces Study the emergence of time
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of results and their communication for different user groups Support users with optimal usage and interpretation of scenario products Profile MSc in natural science or computational science and preferably a
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solid booster formulations with PFAS-free binders, in line with the sustainability goals of the project. You will explore compositions and pellet morphologies to optimize mass transport and reactivity
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optimize, specialize, and deploy models — fine-tuning, distillation, quantization, and efficient inference. Contribute to the evaluation and benchmarking of AI systems on scientific tasks, including open and
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-tuning, or related optimization methods. Experience with cloud infrastructure, MLOps or LLMOps, containerization, or production deployment. Frontend and/or backend development skills. We offer ETH Zurich
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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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performance of large-scale experiments. LLM post-training and Reinforcement Learning Support SFT, preference optimization, and reinforcement learning workflows. Build and run RL environments for tasks with