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Natural Language Processing and Understanding Text mining and information extraction Machine learning Document Intelligence Background in any of the following topics: Financial Technologies Regulatory
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. Research Themes and Projects: We are an interdisciplinary research team integrating single-cell and spatial genomics, lineage tracing, synaptic proteomics, functional perturbation screening, and machine
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for model creation and operation Write scientific articles Supervisory duties Number of staff supervised Category C : 1 Ability to integrate into a project involving more than ten people Computer languages
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experience. Knowledge of machine learning. Notes: Appointment Type: This is a full-time, 2-year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing
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Instrumentation Development System (BIDS). Comfortable in a Linux environment. Knowledge of Rust. Knowledge of quantum information science and experimental and analytical experience. Knowledge of machine learning
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. Program Contact Want to learn more about the MLEF Program? Register for one of our information session s. Visit our website www.energy.gov/fe/mlef for more information on the MLEF Program. Contact MLEF
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: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics
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area a wonderful place to live. Visit the Maine Office of Tourism to learn more about what the Bangor region has to offer. Qualifications: Required: PhD in Ecology, Geography, Data Science, or related
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community health workers (CHWs) with advanced data-driven tools to improve healthcare access and outcomes for high-risk patients. The postdoctoral researcher will play a key role in translating machine
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technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human