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related field completed within the last 5 years. Experience utilizing computational thermodynamic (CALPHAD) software, such as Thermo-Calc, DICTRA, PANDAT, or FactSage. Proficiency in materials data
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Postdoc positions in Organic Chemistry: developing the next generation super materials for sustainable industrial polymer products Department of Chemistry Organic Chemistry Section Faculty
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Posted on Tue, 08/18/2026 - 10:22 Important Info Faculty Sponsor First name: Adam Faculty Sponsor Last Name: Boies Stanford Departments and Centers: Mechanical Engineering Postdoc Appointment Term
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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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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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-mantle NCMASF3 system; ii) Training a Mixture Density Network emulator on 106 thermodynamic evaluations; iii) Implementing a global MCMC Bayesian inversion of the SPARTANS tomographic model; and iv
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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
the following materials as a single PDF document to [email protected] with the subject line "Postdoc Application – [Your Last Name]" Lab: https://parklab.ucla.edu/ Qualifications Basic qualifications • Ph.D. in
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engineering Engineering » Other Physics » Thermodynamics Physics » Other Technology » Energy technology Technology » Transport technology Researcher Profile Recognised Researcher (R2) Application Deadline 31
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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
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learning and expand its safe use in space. This includes, but is not limited to, approaches based on statistical mechanics and thermodynamics of learning, dynamical systems and continuous-time views