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. Areas of interest include—but are not limited to machine learning and deep learning architectures; trustworthy or explainable AI; generative AI and natural-language systems; computer vision and multimodal
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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. Qualifications Applicants must hold a PhD degree in electrical/electronics engineering, telecommunications or related field. Other requirements include: Strong background in wireless communication systems and
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willing to learn from other people in the lab and collaborate. Candidates should have a master’s degree in Molecular biology, Biochemistry, or similar field and have deep interest in molecular biology and
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supporting the academic endeavour from curriculum design to engaging in research/scholarship and providing a student enabling environment. Deep and broad experience in effective clinical teaching and learning
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the world’s largest supercomputers (Polaris, Aurora) and some of the most advanced characterization tools in the world at Argonne and Sandia National Labs. Candidates with a background in deep learning
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practices. Attend lab meetings, seminars, and participate in departmental and university activities as appropriate. Other Duties as Assigned 5% Qualifications Core Knowledge and Abilities Deep expertise in
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other module development relateing to AI-assisted cardiac surgery. Other duties as assigned. Minimum Qualifications Bachelor's degree required. Preferred Qualifications Experience with deep learning
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– Resolution of appeals 16.01.2026 – 4:00 PM – Final results Additional comments We are seeking a PhD student in Machine and Deep Learning for Satellite Image Processing to join our team, who will be
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria The position requires a PhD in machine learning, NLP, causality, or a related discipline, with a strong command of deep