259 computational-physics-"https:"-"https:"-"https:"-"https:"-"INRAE" positions in Switzerland
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100%, Basel, fixed-term The Computational Biology (CoBi) group, led by Prof. Dagmar Iber, develops data-driven, mechanistic models of biological systems using advanced imaging and computational
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scientific publication. Source Data extraction from PDF documents to compile metadata of projects funded under ETH Board Open Research Data (ORD) program Contribute to data packages generated by openwashdata
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. The main research focus of our division is the relationship between physical activity and cognitive performance across development. Possible research topics within this position include, among others
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. Profile Applicants must hold a M.Sc. Diploma (120 ECTS points) or equivalent in civil, mechanical or electrical engineering, geosciences, physics, applied mathematics, computer sciences or related fields
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To submit an application, you need a written confirmation from the research institution. At UZH, you will receive the confirmation letter via the approval process in AVA, the UZH third-party funding
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dynamical systems, and machine learning, with applications to synthetic biology and biomolecular circuit design. Our research develops mathematical and computational frameworks for understanding and
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To submit an application, you need a written confirmation from the research institution. At UZH, you will receive the confirmation letter via the approval process in AVA, the UZH third-party funding
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the Study of Religion: 12 months Faculty of Law: 12 months Faculty of Business, Economics and Informatics: 12 months Faculty of Medicine: 12 months Vetsuisse Faculty: 12 months Faculty of Arts and
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COMPAS XR framework developed at ETH Zürich. Project background The successful candidate will work at the intersection of computational design, XR, human-computer interaction, and robotic fabrication, with
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-dimensional biological datasets, developing and maintaining bioinformatics pipelines, and collaborating closely with experimental scientists to translate computational findings into biological insight