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seek a candidate with strong capabilities in hurricane modeling and risk assessment, and demonstrated experience in one or several of the following areas: Tropical cyclone dynamics and thermodynamics
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into value-added products Design, build, and optimize plasma reactors and related experimental systems. Conduct thermodynamic and kinetic analyses of plasma-driven chemical processes. Perform chemical and
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. - Strong expertise in multiscale/multiphysics modeling relevant to catalysis, and experience with machine learning models. - Deep understanding of reaction kinetics, thermodynamics, and structure-reactivity
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specialists in organic and inorganic synthesis, coordination chemistry, thermodynamics, laser spectroscopy, materials characterization, chemical separations, computational chemistry, and nuclear chemistry. Our
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modeling and risk assessment, and demonstrated experience in one or several of the following areas: Tropical cyclone dynamics and thermodynamics Statistical and/or machine learning approaches to weather
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret
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succesful candidate has the following qualifications: An PhD degree in either applied physics, chemical engineering, mechanical engineering or a similar field Profound knowledge of thermodynamics and/or fluid
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processes Development of phenomenological, thermodynamic, and kinetic models for complex reactive systems Integration of experimental datasets with modeling and simulation frameworks Dynamic simulation and
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science, energy engineering or a closely related field. Solid background in thermodynamics, transport phenomena, and process modelling and computer programming with documented experience in developing and applying
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theory, thermodynamics, statistical mechanics, or non-equilibrium physics Preferred Qualifications: Rich experience with transport measurements and characterization Basic knowledge of models of strongly