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, and contributing to grant applications. The post offers opportunities to work with international research groups and contribute to open-source bioinformatics tools. Experience with deep learning
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to join our team at the CRSA to develop AI models, specifically deep learning approaches, to analyze and predict key climate variables such as precipitation and temperature which are essential
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fellowships and NSF SBE postdoctoral awards. We especially welcome applicants with theoretical interest in child language development, strong computational and analytical skills (deep learning frameworks), and
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degree (or near completion) in Electrical Engineering, Computer Science, or a closely related subject. Research experience in wireless communications and deep learning is essential. The project will also
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quantum chemistry calculations and data-driven materials property predictions. A deep understanding of materials properties and close connections in academia and industry enable the group to explore
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | about 1 month ago
with expertise in medical image processing—particularly registration and segmentation—and proven experience in deep learning, with a focus on ultrasound imaging. Prostate cancer diagnosis relies
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Language Processing, and Electronic Medical Record (EMR) data mining. Prior experience in deep learning, biophysics or omics data analysis is essential. Preference will be given to applicants with prior training in
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) About the Project Deep learning models, and in particular large language models (LLMs), have demonstrated remarkable capabilities but remain limited by their heavy computational requirements, lack
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communication) Willingness to learn and confront new challenges Preferred Qualifications Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal
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, statistics, 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