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the Principal Investigator (Dr. Shengli Zou). Conduct advanced computational chemistry research with a focus on nanophotonics, quantum mechanics, and machine learning–assisted modeling and simulations. Prepare
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Classification Title: Post-Doctoral Associate in unsupervised and generative ML for chemistry Classification Minimum Requirements: PhD in Chemistry or related area Strong coding (Python) and
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, condensed matter physics, or a related field, with experience in first-principles calculations and/or machine learning for materials research being highly desirable. For additional information about this
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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
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, or robotics. • Knowledge of artificial intelligence, machine learning, computer vision, • sensing, data analytics, simulation, human-technology interaction, or cyberinfrastructure. • Knowledge of construction
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proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. ● Pursue research topics such as protecting
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well as general research involving the application of methods from theoretical physics, mathematics, and machine learning with the goal to understand the brain function. Position Requirements Applicants
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About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months 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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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific