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independently and collaboratively Experience with deep learning frameworks, such as Tensorflow or Pytorch is advantageous Effective communication skills and an interest in contributing to a highly international
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pillars such as Big Data Analytics and Management, Machine Learning and Optimization, AI for Data Science, Deep Learning, Generative Learning, Biometrics Processing, Natural Language Processing, Computer
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implement robust AI control architectures (including advanced topics like deep reinforcement learning) for precise motion planning, complex manipulation, and sophisticated sensing/navigation in dynamic
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future business leaders. And we are looking to add to our BIZ family! To learn more about the NUS Business School, please visit https://bschool.nus.edu.sg/ Job Description The Content Marketing Specialist
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optimization techniques. You have experience with modern Deep Learning Frameworks (PyTorch, Tensorflow, Jax) and proven ability of CUDA and Python programming. Knowledge of, or prior experience with, optimizing
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, deep learning architectures, transformers, or LLMs. Familiarity with healthcare data standards (e.g., SNOMED CT, LOINC, RxNorm) or electronic health record systems. Experience with version control (Git
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in deep learning approaches and also experimental experience. Good communication and writing skills & team player. Strong interest in research work. Highly motivated, independent and resourceful. We
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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific vision
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places
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: Experience with probabilistic graphical models, time series analysis, or deep learning Familiarity with reproducible research practices and open-source collaboration Interest in interdisciplinary applications