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measurements; Modeling of indoor pollutant emissions, transport, transformation, and exposure, ranging from mechanistic or mass-balance approaches to more advanced computational models; and Related topics in
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other air pollutants, including source-resolved measurements; Modeling of indoor pollutant emissions, transport, transformation, and exposure, ranging from mechanistic or mass-balance approaches to more
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postdoctoral position is available in the laboratory of Prof. Alex Persat (EPFL School of Life Sciences, https://www.p-lab.science/ ) to establish a new image-based drug screening platform targeting gram
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of life (biosignatures) – whether through remote sensing or direct onsite measurements – requires significant innovation. These challenges demand close collaboration across physics, biology, chemistry and
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research is built around three intertwined questions: how to measure and understand behavior with AI, how brains and embodied agents learn to control the body, and how the brain builds a sense of its body
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this new hybrid network. Your code will directly enable the next generation of energy-efficient AI clusters. Project scope You will bridge the gap between custom optical hardware and standard AI software
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which cells sense, adapt, and respond to their environment. We study free-living unicellular organisms as model systems. Using microscopy, quantitative measurements, and molecular perturbations, we seek