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) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software
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recovery trajectories and injury patterns. Integrate personalized physiological measurements into a recovery prediction model, while adapting Bayesian Neural Networks for SCI data and analyzing the impact on
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, functional genomics, protein engineering, and targeted protein degradation. Project background High-throughput perturbation technologies rely on perturbing DNA or RNA to infer the function of proteins. Methods
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the Swiss Federal Railways via the ETH Mobility Initiative, will assess the ability to improve processes for rail system development to unleash efficiency gains, with specific examples for the cargo sector
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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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to document, track, and disseminate output, maintain and grow our communication channels with engaging content, organize events and outreach activities, and promote engagement with the public and industry. You
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inflammation, tracks environmental exposures and medication adherence, and applies AI/ML models to detect risk, predict exacerbations, and trigger timely, clinician-guided interventions. The project will deliver
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projects. A strong track record of scientific publications. Excellent teamwork, organizational and planning skills, a solution-oriented mindset, and creativity with the ability to innovate. Have social and
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errors Confident working with analytics dashboards, tracking tools, and reporting key metrics (Google Analytics, basic SEO, UTM tagging) Comfortable with custom code integrations or working alongside
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track. We then develop and evaluate a robust cannabis-driving detection model before and while driving. Ultimately, we are working towards a scalable digital biomarker platform for in-vehicle driver state