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, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving
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, machine learning, and pattern recognition. The successful applicant will have: very strong programming skills and experience with deep learning libraries; strong python and object-oriented programming
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l'institut du thorax, INSERM, CNRS, Nantes Université | Nantes, Pays de la Loire | France | 18 days ago
using deep learning approaches. Effectively, in order to prevent cerebrovascular accidents, it is important to study the blood flow at the major bifurcations along the cerebral vascular tree (we mostly
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project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision or physics-informed machine learning, develop robust surrogate forward models to predict
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strong computational–experimental feedback loop central to the project. Subject description Recent breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry
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are looking for a postdoctoral researcher in the field of image generation algorithms (specializing in Deep Learning) for a 12-month position. The work will take place within the IMAGE research team
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–experimental feedback loop central to the project. Subject description Recent breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry, have enabled the creation
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At the Technical Faculty of IT and Design, Department of Sustainability and Planning (PLAN), a Postdoc position in Satellite Data Processing and Machine/Deep Learning is open for appointment from
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to fundamental research in forest imaging and 3D deep learning Base Salary Level A Step 6 – 8 $113,400 - $121,054 p.a + 17% superannuation About the opportunity We are currently seeking a Postdoctoral Research
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 11 hours ago
involves processing and harmonizing high-resolution NASA EO data. Subsequently, we will architect and train an ensemble of deep learning and statistical models capable of identifying key wildfire drivers and