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-cultural. EPFL covers a wide spectrum of science and engineering and offers a fertile sSchool of Basic Sciences include theoretical and experimental biophysics, biological imaging and physics of machine
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the broad landscape of computational science, including artificial intelligence, machine learning, deep learning, and their applications in addressing complex scientific and societal challenges, encompassing
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techno-economic assessments is preferred, and knowledge of applied computational techniques and machine learning methods is a plus. Postdoctoral research experience is preferred but not essential. A
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implementing new informatics tools and resources to enhance phenotyping performance or enable deep phenotyping through terminology/ontology, natural language processing, and machine learning. The role involves
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an outstanding track record or strong interest in the fields of antibody design, structural biology, AI/machine learning, or immuno-oncology, we invite you to apply with a project proposal for a position in our
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utilizes a widely available diffraction-limited spinning disc confocal microscope (although not limited to this modality) for imaging. A single-step, machine-learning based approach is then applied
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materials and devices, calorics, heat transport, and thermal management. Experience with applied computational techniques and machine learning methods is a plus. Some postdoctoral research experience is
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in high-performance computing, materials chemistry, theoretical chemistry, molecular dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive
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computational chemistry and materials science, with a focus on the use and development of computational and machine learning methods, who has a critical eye, a deep understanding of their subject and interests
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automation software for high-throughput quantum-hardware preselection and characterisation using image recognition and machine learning tools. As R&D institution we are highly interested to disseminate