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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the channels
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
Demonstrated research experience in machine learning, deep learning, medical image analysis, computer vision, biomedical data science, or a closely related area. Strong programming skills in Python and
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learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop and train deep learning models (CNNs, ...) data to predict IPLSs
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design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale microbiome and genome
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
, Competencies, and Experience Strong research background in computer vision and multimodal machine learning. Experience with deep learning and multimodal/vision-language models. Strong programming and research
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | 4 days ago
environment. For the Bonobo Behavioral Ecology Research Group at the Max Planck Institute of Animal Behavior, we are looking for a highly motivated Postdoc. The workplace will be in Konstanz, Germany
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as a member of the GHER contributing to the EU research project COMEDI in a consortium of 11 leading partners in the field of data assimilation and deep learning. A successful applicant will develop
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Sujet de stage This postdoc aims to enhance PULSE, a generative (VAE) method revolutionizing predictions for disordered materials. You'll improve its accuracy, uncertainty quantification, and transition
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark