52 phd-mathematical-modelling Postdoctoral positions at Pennsylvania State University
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. Candidates must have a PhD in MatSE and experience in developing phase-field models of microstructures and properties by start date. This term position is funded for one year from the date of hire with
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reporting. Candidates must have a PhD in MatSE and experience in mechanics of materials, computational modeling, and experimental characterization of materials. Candidates should submit a CV and cover letter
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students. The required qualifications are: PhD degree in mathematics, science, engineering, or a related field by the start date. Extensive experience in one or more of the following areas: probabilistic
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models for fracture propagation, reactive transport, and reservoir-scale hydrogen yield prediction. Design and implement data acquisition systems and sensor integration for experimental campaigns. Prepare
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SPECIFICS Postdoctoral Researcher in Defect Modeling The Pennsylvania State University Department of Nuclear Engineering The Computational Nuclear Materials Group (https://sites.psu.edu/cnmg/ ) at Penn State
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. Requirements and Qualifications: The Postdoctoral Scholar must have a PhD in transportation engineering, operations research, mathematics, or a related field by the appointment start date. In addition, the
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modeling, life-cycle assessment and/or techno-economic analysis of agricultural, forestry, and bioconversion systems at The Pennsylvania State University. The Postdoctoral Scholar will work in the
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independently and collaboratively. Preferred Qualifications A strong background in AI/machine learning, mathematical modeling, and programming. Extensive practical experience in AV development, testing
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%): Generating academic outputs, such as presentations, grants, and manuscripts. 4) Related tasks (10%): Other related tasks assigned by the principal investigator. Eligibility: Candidates holding a PhD degree in
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: PhD in Biology, Neuroscience, Systems Biology, or a related field with a focus on neurodevelopment, transcriptomics, or systems biology. Strong background in mouse models and neurodevelopmental