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, analytical modelling, and numerical simulations to develop and validate novel reinforcement systems. This position is part of an Innosuisse-funded collaborative project with industry partners, focusing
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modeling tools (GEOS-Chem and CESM) and analysis of large observational datasets. The biosphere represents an important source of many reactive trace gases and aerosols (e.g. soil NOx, bioaerosols, BVOCs
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new type of image sensor based on perovskite materials. Related publications: 1. Tsarev, S., et al., Vertically stacked monolithic perovskite colour photodetectors. Nature, 2025. 642(8068): p. 592-598
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the technical implementation, the candidate will contribute to the development of regulatory frameworks, business models, and social analyses that enable broader adoption of community PV. This interdisciplinary
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. You will incorporate field survey data, remote sensing and other auxiliary data into spatial modelling processes using techniques such as species distribution modelling and artificial intelligence
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transduction, cell culture, and immune functional assays; supporting the development of in vivo models, such as adoptive T-cell transfer in mice, for preclinical testing of engineered circuits where relevant
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. You will perform microstructural characterization of dry coated electrodes using physical and machine learning based methods and the electrochemical assessment of the electrodes in battery cells. Your
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in these areas. It is anticipated that the work will be based at CERN for a major portion of the duration of the appointment. There may be opportunities for some presence at the Fermilab LHC Physics
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. Opportunity to interact with internationally renowned experts, and with a strong team of postdoctoral researchers and PhD students. The candidates should have A Ph.D. in Mathematics (be near completion). A
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probe tomography or scanning probe microscopy. Your profile You hold a PhD in Physics, Materials Science or similar. A high level of motivation to work in close collaboration with industry