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Field
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opportunity promises deep academic inquiry, industry collaborations, and the chance to influence future practices and research directions in these fields. Key Responsibilities: Develop robust mathematical and
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field with a strong background in AI, machine learning, or deep learning). Demonstrated experience with CFD and/or FEA, particularly in biomedical applications preferred. Proficiency in programming
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
generation and Q&A/dialogue, and interpretable and generalizable deep learning. The duties of the postdoctoral scholar will include aiding the research of graduate students on NLP+ML projects and leading
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information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software tools and products. Experience in writing scientific papers and successful
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contributing to multiple projects including resilience-aware scheduling, deep learning workload job scheduling, and storage system performance tuning. The candidate will have the opportunity to engage in
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school with deep roots in the Nordic socio-economic model. Our faculty has a broad focus on societal challenges, and we have earned a reputation for high-quality disciplinary and interdisciplinary research
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electrophysiology to investigate the neural substrates of motor learning in healthy subjects and during stroke recovery. Competitive applicants will have experience with one or more such techniques and a track record
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-of-the-art foundation models and large vision-language models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
/missing data, and interpretable deep learning. The duties of the postdoctoral scholar will include aiding the research of graduate students on multimodal ML projects and leading research directions
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discipline. The candidates will have expertise in computational imaging, with: (i) an algorithmic focus, with particular interest in methods at the interface of deep learning and optimisation theory, and/or