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experimental work in chemical or process engineering (desirable) Knowledge of process optimization, parameter estimation, or control methods is a plus Programming experience in MATLAB and/or Python Familiarity
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curious to deliver work that matters, your journey starts here! The Department of Electrical and Computer Engineering (ECE) ranks among the best in the country. Our research programs are at the forefront
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-efficiency to realized efficient Embodied/Edge-AI implementations. A key focus will be on investigating novel methods with strong theoretical foundations as well as their full-system deployment in real-world
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methods, provides the ideal environment for research on programming with formal guarantees — a topic of increasing practical importance. About us The Department of Computer Science and Engineering , a joint
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, uncertainty-aware parameter estimation, surrogate modeling, and reduced-order modeling where relevant. The scientific emphasis is mechanics-first: we are looking for someone with strong foundations in nonlinear
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, transitions of control, driver awareness, and the communication of system capabilities and limitations. The project brings together expertise from human-computer interaction, AI, human factors, cognitive
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 20 hours ago
research in close conjunction with NETL federal and contract staff to: (1) test and validate open-source methods for extracting structured data from scanned records; (2) integrate open-source large language
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, and research method innovation. The collaborative expertise of the postdoctoral associate cohort, using both qualitative and quantitative methods, will contribute to, for example, foundational research
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studies using qualitative, quantitative, and mixed-methods approaches, including surveys, interviews, observations, social network analysis, and analysis of digital trace data. Collaborating with industry
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 20 hours ago
, increased storage) Apply geostatistical methods (e.g., kriging) to characterize the spatial heterogeneity of key reservoir parameters (e.g., porosity, permeability) and quantify subsurface uncertainty through