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optimal new technologies and transition pathways simultaneously. To holistically evaluate the environmental impacts of processes and energy systems, we develop predictive methods for Life Cycle Assessment
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laboratory environment, primarily at BSL-1 with potential work at BSL-2, by following safety regulations, collaborating with team members, and optimizing workflows. Professional training as a Laboratory
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, showcases and deep dives for SNAI offerings) to optimize and grow the partnership and membership base. Manage accounts, be the single point of contact and connector for the members and facilitate
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-stakeholder collaboration across phases to improve decisions. Methods may include AI/ML (incl. LLMs), XR, robotics, simulation, optimization, or others that fit your research question. We welcome foundational
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and additives Optimize melt-spinning, uniaxial stretching, and post-treatment steps to control sheath porosity and ion diffusion Acquisition of research grants and writing of scientific publications
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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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-transportation system, we are looking for a: PhD Student in Data-Driven Policy Optimization for Transportation and Energy (100%) Project background Our energy and transportation systems are rapidly transforming in
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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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are working closely together with ETH researchers to provide support in the wide area of scientific computing from data management and analysis, development of scientific software, to porting and optimizing
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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