20 parallel-computing-numerical-methods positions at EPFL in Postdoctoral in Switzerland
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at international conferences and workshops Position 1: Computer Vision & AI for Behavior Analysis Contribute to the creation of behavioral datasets for groups of animals Develop methods for animal and environment
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoctoral Position in Computational Genomics, Machine Learning & Single-Cell Biology Mission
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and in computer architecture domains, our ability to analyze data still falls behind the unstoppable data collection rates. Data-intensive applications are increasingly more demanding in sophisticated
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to 3D transistor architectures and stacked, hybrid-bonded devices, non-destructive, high-resolution 3D imaging is becoming a necessity. Unfortunately, current 3D X-ray nanoimaging methods
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with a focused on micro-technologies. To strengthen our research program on laser-based methods to tailor material properties, we are looking for a post-doc to investigate advanced wavefront shaping
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, engineering, computer science, or a related field. Experience with inverse problems and 3D reconstruction methods for tomography, laminography, or a closely related modality. Strong scientific programming in
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, engineering, computer science, or a related field. Experience with inverse problems and 3D reconstruction methods for tomography, laminography, or a closely related modality. Strong scientific programming in
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political implications of vertical urban development. The project has three main ambitions: (1) developing methods to measure verticality and its impacts in data-scarce contexts, in Africa and elsewhere; (2
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Modelling (BIM), Geographic Information Systems (GIS) or computer programming is a plus. A master's degree or professional experience in architecture is preferred but not required. The employment rate varies
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Understanding human motivation requires methods that go beyond questionnaires and simplified computer-based tasks. This project aims to develop more naturalistic, yet highly controlled, behavioral assays in which