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simulation environments (e.g., CARLA). • Domain knowledge in ITS, traffic engineering, autonomous vehicles, robotics, or related areas. • Experience using cloud platforms for training and deploying AI models
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Engineering, Computer Science, or a related field. Accompanying Knowledge, Skills, Abilities and Competencies Excellent abilities in molecular modeling and simulations (molecular dynamics or Monte Carlo
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activities . You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 6 hours ago
USNH Employees should apply within Workday through the Jobs Hub app The research position(s) are within the broad area of biophysics, structural modeling, and molecular dynamics (MD) simulations
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, including parameter optimisation and advanced monitoring techniques. Develop and refine process models, simulations, and automation strategies. Characterise microstructure, wear behaviour, and corrosion
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full-wave simulations and characterize the relevant metamaterial structures. Extend existing analytical tools and numerical models. Prepare and publish scientific articles and reports and co-supervise
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
on accelerated molecular simulations and AI-driven drug discovery. Research projects in the Miao Lab include development of novel theoretical and computational methods and AI techniques for accelerated simulations
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
Department of Pharmacology at the University of North Carolina – Chapel Hill (http://miaolab.org ) is looking for a highly motivated Postdoctoral fellow to work on accelerated molecular simulations and AI
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learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in porous materials Develop novel machine learning model for predicting
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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a