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Field
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and Applied Sciences Department/Area Electrical Engineering/Computer Engineering/Computer Science Position Description Project Deep learning plays an essential role in the operation of an autonomous
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and provide relevant information to inform NIST management and stakeholders - Maintain deep technical knowledge of advances in the application of artificial intelligence and machine learning
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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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Job Description Job Alerts Link Apply now Research Analyst/ Associate/ Fellow in Machine Learning and Artificial Intelligence (ML/AI) University-Level Unit: Sustainable and Green Finance Institute
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-funded AI research group “Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (DeSBi)” development of deep neural networks and machine learning algorithms for the analysis
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leadership, shared responsibility, and a deep commitment to genuine care and respect for our community. Find out more about our vision for a truly inclusive workplace in our Diversity, Inclusion and Belonging
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Biology, Bioinformatics, Statistics, or a closely related discipline, and have an strong record of research productivity. The ideal candidate will have experience in deep learning, generative models
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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reproducibility, Knowledge of deep-learning methods, At least one first author manuscript in the context of omics data analysis in an international peer-reviewed journal in good track for publication (to be
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& Responsibilities: Develop advanced deep learning methods for radiology or pathology medical imaging Integrate imaging data with EHR, clinical notes, or genomic data Conduct research on segmentation, classification