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through the electronic application process. Each recommendation consists of two elements: A form to be filled out by the referee An additional letter with the referee’s comments Your referees
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for a reliable, enthusiastic, and highly motivated postdoc with a passion for science to join our team in Zurich. Our research focuses on process- and system-understanding of the biosphere-atmosphere
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for Hamiltonian matrix prediction to treat dynamical matrices. This ML framework will then also allow us to produce the derivatives of both quantities, which correspond to the electron-phonon and anharmonic phonon
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. You will work on this project with a PhD student, whose main task will be to develop a process-scale representation of radiative transfer in firn, while your focus will be on implementing and
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Measurements of muonic X-rays from low-Z elements within the QUARTET collaboration Operation and further development of a metallic magnetic calorimeter MMC onsite at PSI Studies for the use of the MMC across
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processing large datasets or experience in high-performance computing (HPC) is an advantage Experience with weather and climate applications and weather ensemble forecasting is an advantage You are creative
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. Strong programming skills in Python and familiarity with a modern ML stack (e.g., PyTorch, hydra, zarr, dask) Experience in handling and processing large datasets or experience in high-performance
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Ph.D. Position in Organic Chemistry, Polymer Chemistry, and/or Sol–Gel Chemistry & Materials Science
energy-related applications. Our research portfolio spans fundamental materials chemistry, process–structure–property relationships, and application-driven R&D, in close collaboration with academic and
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modeling, laboratory experiments, and theoretical analyses, we seek to link microscopic processes with the macroscopic behavior of both engineering and natural systems and develop predictive tools
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modeling, laboratory experiments, and theoretical analyses, we seek to link microscopic processes with the macroscopic behavior of both engineering and natural systems and develop predictive tools