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Field
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experiments or existing data. In this research, the Post Doctoral Scholar may employ recent interpretability methods such as causal interventions, dictionary learning and circuit analysis, but other kinds
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data science, and/or public health or related fields including health services research, health informatics, computer scienceExperience in data analysis using statistical software & machine learning (e.g
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doctoral degree in Computer Science or Biomedical Informatics or a closely related quantitative field. The successful candidate demonstrates documented expertise in machine learning and distributed
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 5 hours ago
Education & Experience: PhD in Computer Science, Visualization, Cartography, Geographic Information Science, or a closely related field. Strong background in visualization, computer graphics, or perceptual
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materials modeling and mechanics, including molecular simulations, multiscale modeling, and/or machine‑learning‑based materials design Demonstrated publication record in peer‑reviewed journals relevant
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, United States of America [map ] Subject Areas: Engineering / Computational Science and Engineering , Machine Learning , Quantum Science and Engineering Appl Deadline: (posted 2026/03/05 05:00 AM UnitedKingdomTime, listed
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remote sensing data analysis and geographic information systems. Experience in machine learning motivated algorithms and quantitative data analysis. Strong writing and communication skills. What You Need
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research program in Artificial Intelligence (AI) and Mathematics. This position involves applying machine learning tools, particularly reinforcement learning (RL), to address complex research-level
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work is studying how undergraduate STEM courses can be tailored to meet the needs of all learners. Current projects involve studying STEM instructor perceptions of student-centered learning as
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). The work spans: Close collaboration with researchers in neuroscience, engineering, and ethics. Human-in-the-loop brain/muscle-machine experimentation focused on learning pedagogy for adaptive neural systems