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funding availability. Responsibilities • Design and implement deep learning architectures, AI agent pipelines, and computer vision algorithms to achieve project goals (33%) • Conduct full stack development
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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 20 days ago
equivalent doctorate (e.g., Sc.D., M.D.) Preferred Education Skills and Experience: Ph.D. in design-related discipline, specializing in deep learning and biometrics. A strong background with evidence of
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project - “Deep learning-based approach for process parameter optimization of SiC wafer under limited data”. He/She will carry out research in the areas of machine learning and data science, and also be
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of Efficient Learning for computer vision Coding Skills: Familiar with any of the major deep learning libraries, including Pytorch We regret to inform that only shortlisted candidates will be notified. Hiring
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positivamentela experiencia/conocimiento en algunas de las siguientes áreas: lenguajes de programación (Python, JavaScript), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas
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electronic health records (EHRs) from multiple UK hospital centres using advanced data analytics including machine learning, deep learning, and statistical techniques—with a particular emphasis on deep
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of machine learning (including deep learning) algorithms to predict links between gene clusters and metabolites, and to predict antimicrobial activities associated with these Collaboration with international
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | 3 days ago
(denoising, Mueller matrix calculation/decomposition) and AI-based diagnostic algorithms using machine/deep learning. The primary challenge will be to deliver practitioner-relevant cervical images in under 0.5
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of our scientists and this job is a unique opportunity to learn about genomics, genome editing, and protein engineering while contributing to the development of future individualized genomic medicines
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Development of machine learning (including deep learning) algorithms to predict links between gene clusters and metabolites, and to predict antimicrobial activities associated with these Collaboration with