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: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
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to the collaborative TQT research community. Principal Investigator: Dmitry Pushin Project Name: Structured matter-wave and electromagnetic wave beams and their applications. Research Area: Experimental condensed matter
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, model and simulate physical processes, and engage in productive discussions with theoretical quantum physicists. Demonstrated programming skills for data acquisition and processing, e.g., Python, Matlab
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help to realize them experimentally on our quantum simulator. We are especially interested in simulating quantum many-body models relevant to materials science and condensed matter physics. We are also
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condensed matter physics and neutron scattering Relevant Fields: Phase transitions, topological materials, neutron optics, matter wave interferometry Required skills: Hands-on experience with low temperature
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fabrications, low-temperature cryogenic transport measurements, Design/Modeling of CNT quantum electronic devices Relevant Fields: Physics, Chemistry, Material Science Engineering, Chemical Engineering, Electric