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of adaptive radiation and associated key innovations in the evolution of freshwater diatoms. By integrating morphology, physiology, genomics, transcriptomics, and computational modeling, we aim to (i) determine
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physics, optics, photonics, materials science, or a related field. Strong experimental skills in optics, spectroscopy, microscopy, or related areas. Experience in programming and data analysis using Python
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Division Macroeconomic Forecasting and Data Science analyses and forecasts the Swiss and international economy and produces KOF’s short- and medium-term macroeconomic outlooks using macroeconometric models
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. Empa is a research institution of the ETH Domain. Empa's Laboratory of Biomimetic Membranes and Textiles is a pioneer in physics-based modeling at multiple scales. We bridge the virtual to the real world
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Simulation Framework The Computational Biology (CoBi) group, led by Prof. Dagmar Iber, develops data-driven, mechanistic models of biological systems using advanced imaging and computational tools. Our group
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field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision of students Your
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in physics-based modeling at multiple scales. We bridge the virtual to the real world by multi-parameter sensing and creating digital twins of heat-sensitive biological systems (food, humans) that can
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anthropology and social science to biostatistics and mathematical modelling as well as observational cohorts with biobanks. The Environmental Exposures and Health Unit (EEH) of EPH is focused on research related
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scanning probe instrumentation fabrication of van der Waals heterostructures transport, optical spectroscopy, and quantum sensing experiments data analysis, modeling, and scientific communication
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: Position Type: Student programs Position Location: Lausanne, Vaud 1015, Switzerland [map ] Subject Area: Fluid Mechanics Appl Deadline: 2025/12/15 11:59PM (posted 2025/07/24) Position Description: Apply