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and experience in machine learning, computer vision, and deep learning methods Excellent English language communication skills, both oral and written Ability to work independently and as part of a
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learning for intelligent transportation infrastructure and systems. Experience and expertise in human mobility simulation and prediction with agent-based modeling and deep learning techniques. Proficient
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We are seeking a postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
quantitative background and a track record of first-author publications in peer-reviewed journals -Experience designing, training, and evaluating deep learning models in Python (PyTorch preferred
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research findings. About you You will have: PhD (or near submission) in computational biology, machine learning, computer science, statistics or a related quantitative discipline. Experience developing and
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candidates with A PhD in machine learning, computer science, applied mathematics, statistics, physics, engineering, or a closely related field, completed or near completion. Demonstrated expertise in
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components of the corn breeding program. This requires a Ph.D. with excellent knowledge and skills in drones / UAV / UAS data collection, processing, statistical analyses, AI (machine learning, deep
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components of the corn breeding program. This requires a Ph.D. with excellent knowledge and skills in drones / UAV / UAS data collection, processing, statistical analyses, AI (machine learning, deep
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taking part in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, scientific computing, statistics, physics or a related
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-image registration , high-performance computing, or GPU-based computation. Familiarity with machine-learning or deep-learning methods for medical-image segmentation. Previous experience in thermal