36 pattern-recognition "https:" "CMU Portugal Program FCT" Fellowship positions at University of Michigan
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of sensor modalities in real-world environments, including smart system, healthcare monitoring, and activity recognition. The candidates will have opportunities to work with outstanding collaborators at all
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, Training or work experience in medical imaging, digital image processing, computer vision, pattern recognition, artificial intelligence, machine learning, deep neural networks, and statistics, Hands
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Apply Now How to Apply Please apply via this Submission Form by copying address into your browser: https://forms.gle/w6xrkTy6Dz6E6xk38 In addition, please add your application materials by
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based within the Supporting Transition and Employment Pathways Research Lab (STEP; https://step-lab.ssw.umich.edu/ ), an interdisciplinary research group dedicated to advancing disability inclusion by
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qualifications, experience, research domain(s), including professional and academic experience, and near term goals Link to a portfolio, containing relevant design work done professionally and/or academically and
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Website: https://yadlapallilab.org ? Publications: https://scholar.google.com/citations?user=otQ6T6gAAAAJ&hl=en Why Join Us? The Yadlapalli Lab offers a unique opportunity to conduct research
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close mentoring, fellows strengthen skills in study design, execution, and manuscript/presentation development. We actively support high-impact publications, conference presentations, and fellowship
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multidisciplinary team focused on accelerating drug discovery with data-rich and automated chemical methods for ecosystem health. See https://www.youtube.com/watch?v=W4HxzWaK1Vo . We are a medicinal chemistry lab
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* The Research Fellow will conduct advanced research under the supervision of Dr. Au, contributing to project design, execution, analysis, and dissemination. Key responsibilities include: Design and conduct
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computational modeling, which is a collaboration between Dr. Brennan, and Dr. Edith Kaan at the University of Florida. The project description is available at: https://www.nsf.gov/awardsearch/showAward?AWD_ID