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an excellent work ethic and background in molecular simulation and machine learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in
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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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-the-house core-level spectroscopy, i.e. X-ray Photoelectron Spectroscopy, X-ray Adsorption Spectroscopy, etc., as well as chemistry domain knowledge, to come up with a unified mechanistic explanation that is
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observations from in-the-house core-level spectroscopy, i.e. X-ray Photoelectron Spectroscopy, X-ray Adsorption Spectroscopy, etc., as well as chemistry domain knowledge, to come up with a unified mechanistic
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, (ii) environmental modeling and/or advanced data analysis and statistical evaluation techniques, and (iii) treatment of water and soils containing organic contaminants using adsorption or other
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-performance adsorption but also catalytic breakdown of these resilient pollutants. Two structurally distinct MOF systems will be developed, each offering different pore architectures and functional groups
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pathogens in water, soil, plants, and sludge. Environmental processes, including adsorption, advanced oxidation/reduction, and biological treatment. Advanced or renewable materials, including biochar and
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/articlehtml/2019/gc/c9gc01844a The successful candidate will evaluate adsorption resin-based ISPR, electrochemical pH-swing ISPR, and other methods to recover a bio-based carboxylic acid that will contribute
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-principles and atomistic simulations with machine-learned interatomic potentials to: Model reaction pathways on metal-oxide surface, including adsorption, reactions and diffusion steps. Construct atomistic
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of biopolymer or polymeric adsorption materials, particularly selective adsorbents Demonstrated ability to publish high-quality scientific papers in peer reviewed journals Demonstrated ability to work