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Massachusetts. Specifically, this fellowship is focused on machine-assisted visualization. We welcome applications from recent PhD graduates who are interested in these or related fields, particularly those who
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investigators to acquire essential academic credentials and research skills with the purpose of increasing competitiveness for MD, PhD, or MD-PhD programs in biomedical sciences. Primary Responsibilities Devote
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, Geography, Civil Engineering, Computer Science, Mathematics, Physics or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning
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duties as assigned. REQUIREMENTS: REQUIRED: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong programming skills. Strong background in machine
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rapid technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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postdoctoral fellowship, starting September 2026. We welcome applications from recent PhD graduates (PhD in hand between September 2021 and September 2026) working in all areas of the Humanities related
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/HCI: PhD in Computer Science, Human-Computer Interaction, Information Science, or related computational fields with expertise in machine learning, natural language processing, human-AI interaction
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date to be determined. Basic Qualifications A PhD related to programming languages by the start date. Experience in machine learning and formal verification. Individuals with a demonstrated track record
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about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Develop DNA-based sensors that seed crisscross assembly of single