-
healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics
-
the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins using physics-informed learning approaches, with specific applications to intelligent transportation
-
Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel excavation and ground response (e.g., geotechnical centrifuge testing, lab-scale TBM experiments
-
learning theory to join the research team of Prof. Muhammad Umar B. Niazi. The position focuses on the design and implementation of incentive mechanisms for sociotechnical and cyber-physical-human systems
-
monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical
-
structural centrifuge testing and physical modeling. Advanced instrumentation and experimental simulation. Successful candidates must hold a PhD degree in Civil, Structural, Mechanical, or Material Engineering
-
. The project activities will involve the development of the theory and implementation of the advanced mechanics and numerical models as well as constitutive model calibration and validation based on physical
-
on the physical layer design of programmable metasurfaces enabled wireless communication systems. The candidate will investigate the role of programmable metasurfaces as reconfigurable holographic surfaces (RHSs
-
, and medical insurance and educational subsidies for dependents. The preferred starting date of the appointment is May 1, 2023 or at the earliest (negotiable). Applications will be reviewed on a rolling