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Field
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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
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, including presenting research findings to diverse audiences and contributing to collaborative discussions expertise in deep learning techniques with experience applying neural networks or related methods
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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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communication Demonstrated track record in scientific writing and publishing We also appreciate the following know-how and experience in: Experience from machine and deep learning data analysis Experience from
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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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Veterinary Medicine ● Variant discovery and genome annotation: Apply deep learning and graph-based models to improve variant calling, transcriptome annotation, and functional prediction in veterinary-relevant
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experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer architectures, attention mechanisms, and fine tuning techniques for LLMs. Experience with time
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours 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
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, Greninger Lab Position Details Position Description The Greninger Lab at the University of Washington is seeking a Postdoctoral Scholar driven by curiosity, eager to dive deep, think big, and learn fast - a
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controls, using deep learning and explainable AI Communicate and discuss results with stakeholders to integrate the findings into water management practices Interpret, publish and present findings in peer