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Position Overview School / Campus / College: School of Medicine Organization: Laboratory Medicine and Pathology Title: Postdoctoral Scholar, Department of Laboratory Medicine and Pathology, Bekris
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strong command of data wrangling, cleaning, and large-scale dataset management. Machine Learning/Deep Learning: Experience with PyTorch, TensorFlow, or Hugging Face; embedding models; and model validation
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description In this postdoctoral position, you will
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. Training LLMs, large-scale deep learning systems, and/or large foundation models using GPU/TPU parallelization while setting up the environment/system network under various constraints, such as limited
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written. Additional Qualifications ConsideredEmpty heading Knowledge of CUDA. Knowledge of PyTorch or a similar deep learning framework Experience writing software trigger infrastructure. Experience
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related to staff position within a Research Infrastructure? No Offer Description Description of the workplace Automatic Control is an exciting and broad subject, covering both deep mathematics and hands
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of postdoctoral research experience and demonstrate capabilities to work independently, to establish and lead the research group. Enrich ongoing work at VU and FTMC laboratories via international cooperation and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https://unc.peopleadmin.com/postings/310186 Posting Contact Information Department
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 21 minutes ago
, robustness, calibration, bias/fairness, and/or adversarial stress-testing. - Solid programming and ML/NLP engineering skills in Python and ideally modern deep-learning stacks (e.g., PyTorch/JAX, HuggingFace