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Intelligence in Mechanics and Manufacturing (AIMM) at ETH Zurich, is offering a position in the field of data-driven optimization. Project background Our research focuses on the development and application
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. The focus is on developing AI-supported, sensor-based solutions for real-time monitoring and optimization of manufacturing processes. These solutions aim to assess process conditions during production
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currently seeking to hire an HPC Optimization Specialist. The objectives of this position are twofold: on the one hand, to extend our HPC user support to help researchers to run their applications and HPC
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We look forward to receiving your application with the following documents as a single PDF: A cover letter indicating which track you are applying for (RL/Optimization, LLM/Knowledge or both) CV
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the laboratory's past and ongoing work within the context of AI-guided Design, Inverse Design, and Optimization across different application domains. In particular, we are developing scientific research
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would build upon the laboratory's past and ongoing work within the context of AI-guided Design, Inverse Design, and Optimization across different application domains. In particular, we are developing
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the bacterial import process, optimizing the system for high performance, and then applying it to problems around therapeutic peptides and proteins. The focus of the work is experimental and will include a broad
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of this project will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The doctoral student position we
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worldwide in industrial and academic research labs for device and material optimization as well as for the study of device physics. Leading manufacturers and academic institutes rely on our tools for electro
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programming, modelling, and data analysis skills. Experience with formulating and solving mathematical optimization problems is an asset. Proficiency in English is required; good comprehension and oral skills