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, molecular dynamics simulations using ab initio and machine-learning potentials, and the development or application of machine-learning tools for feature extraction, property prediction, and inverse molecular
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plasmas, including via methods based upon Molecular Dynamics and Particle-in-Cell techniques as well as experiments. We also envision that the ideal candidates will provide support to experimentalists and
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specializes in fluorescence and Raman-based approaches, integrating advanced microscopic analysis to gain molecular-level insights into complex materials and systems. The lab is internationally recognized
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photo-bases. The work will focus on modeling of adiabatic and nonadiabatic photochemical processes to capture excited states dynamics using an array of ab initio molecular dynamics methods for excited
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property prediction, modern artificial intelligence methods, molecular dynamics, and interdisciplinary research, this is your chance to be part of an exciting journey at the forefront of science and
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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preferred, but not required) are desired. Experiences with catalysis (biological, homogeneous, or heterogeneous), excited-state simulation methods, multiscale simulations (broadly defined), molecular dynamics
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
to work 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