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environments. The project will explore how learning-based and agentic AI systems (e.g., agents built on large language or foundation models) can be combined with physics-informed process models, digital
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LTS2 Lab https://lts2.epfl.ch offers a highly motivating, interdisciplinary scientific environment with many opportunities to interact between different projects and researchers, and has an
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are most important for the use of solar energy. https://www.epfl.ch/labs/sci-enac-as/ Main duties and responsibilities As a PhD Student, you will be expected to: Assume full responsibility for your
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use of solar energy. https://www.epfl.ch/labs/sci-enac-as/ Main duties and responsibilities As a PhD Student, you will be expected to: Assume full responsibility for your PhD dissertation; Perform
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, including physics-based modeling across scales (discrete/mesoscale/continuum), thermodynamics-informed machine learning and neurosymbolic AI. They will also have the opportunity to lead international
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assistantship Part-time supervision of MSc students Profile A master degree or (equivalent) in atmospheric, climate, or environment science, engineering, meteorology, physics or similar Interest in
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interdisciplinary aspects that demand a highly motivated candidate with strong analytical abilities that can think out of the box. The successful candidate has a background in photonics, physics, chemistry
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photonics, physics, chemistry/material science, electrical or bioengineering. Experience in nonlinear optics / microscopy, or ultrafast spectroscopy is a bonus. We offer excellent working conditions and a
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work at national and international conferences. Maintain collaborations and deliver periodic reports that describe your progress within the project. Profile Physics background, strong interest in high
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composites, ceramics, and metals (Composites: https://doi.org/10.1016/j.matt.2026.102809 , https://doi.org/10.1021/acsmaterialslett.5c00407 ;Ceramics/Metals: https://doi.org/10.1002/adma.202504951