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for establishing correctness with respect to formal specifications Engineering efficient implementations that make high-level abstractions practical We seek outstanding candidates working in programming languages
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AI-assisted proof engineering. The position is part of an ARIA-funded collaboration between EPFL and Imperial College London whose goal is to build a formally-verified ML inference engine
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infection models to identify and characterize compounds active against these priority pathogens. Main duties and responsibilities Design and build a microscopy-based phenotypic screening pipeline (live
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indoor air quality, aerosol science, exposure science, and healthy buildings. Projects may combine controlled laboratory experiments, measurements in real-world buildings, data analysis, and modeling
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advanced computational models; and Related topics in indoor air quality, aerosol science, exposure science, and healthy buildings. Projects may combine controlled laboratory experiments, measurements in real
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, building technology, material science or a related discipline. Candidates without a PhD but with equivalent research experience and expertise may also be considered for an alternative appointment as a
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a new research collaborator with a PhD in building technology, preferably in the field of building materials and/or building envelope performance and/or building renovation. The candidate must be
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present your work internationally. You are the ideal candidate if You hold a PhD in mathematics, computer science or a related field You have a strong background in formal verification with Lean You have
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discussed with the successful candidate depending on their background, expertise and affinities Analysis and publication of results Build a strong network in the field of research Participate in education
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→ future urban scenarios The research will operate across city, neighbourhood and building scales and along urban transects covering historical central districts, incrementally verticalising neighbourhoods