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Field
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-inspired approaches for modeling, designing, and predicting the response of composite systems. Responsibilities: Develop AI approaches for predictive multi-physics response of composites in Energy
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morphing-wing UAV prototypes. Methodology: Design and Simulation: ABAQUS, SolidWorks, ANSYS, or COMSOL for topology optimization and aerodynamic modeling. Fabrication: Composite layup, 3D printing (FDM/SLA
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material property database for composites. The candidate will utilize the database to develop AI models for composite discovery. The candidate will work with a multidisciplinary team to set up finite element
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compositional reasoning. The core research thrusts of this position are: • Structured, neurosymbolic models: The research will investigate model architectures that are not learned from a blank slate. Instead
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. The research assistant will: Participate in CAD/CAE modeling and structural optimization of UAV frames. Contribute to fabrication using composite and polymer additive manufacturing. Prepare and execute
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composition and atomistic modeling of materials. The main activities will include: - formulating new descriptors of critical temperature (Tc) incorporating electronic fluctuation effects, evaluated by
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solar (thermal and PV) and geothermal energy with soil-based thermal storage to enable reliable 24/7 operation of adsorption desalination. We also develop low-cost sorption composites from locally
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information about this on the UK Visas and Immigration Website . The University of Reading is seeking to recruit a PDRA in Holocene Vegetation Modelling to apply an eco-evolutionary optimality model of gross
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candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage
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, developing molecular models of electrolytes based on polymers, LiFSI salt, and ionic liquids, in contact with active material surfaces. Simulations will be carried out in confined geometries representative