Job ID: 141795

Ph.D. positions for Reduced Order Modeling, Machine Learning, and Optimization

University of South Carolina

  • May 9, 2020
  • Ph.D. positions for Reduced Order Modeling, Machine Learning, and Optimization
  • Mechanical Engineering
  • University of South Carolina
    Columbia, SC
  • Dec. 1, 2020
  • Fall 2020 and Spring 2021
  • Post-Doc
  • Water Resources Engineering
    Transportation Engineering
    Sustainable Engineering
    Structural Engineering
    Ocean Engineering
    Naval Architecture & Marine Engineering
    Mechanical Engineering
    Manufacturing & Quality Engineering
    Industrial & Systems Engineering
    Engineering Physics
    Engineering Mechanics
    Energy Technology
    Electrical and/or Electronics
    Civil Engineering
    Bioengineering (all Bio-related fields)
    Engineering - Other

Ph.D. Research Assistant positions in Mechanical Engineering are available in Fall 2020 and Spring 2021 within the research group of Dr. Yi Wang at the University of South Carolina-USC (Columbia/Main campus,

Reduced Order Modeling, Machine Learning, and Design Optimization for Multiphysics Engineering Systems
We will investigate and develop reduced order modeling, machine learning, and design optimization methods for multiphysics systems for a variety of engineering applications, which include but not limited to thermal-fluidics, aerospace and aeroservoelasticity, energy materials and management, additive manufacturing, and microfluidics & nanofluidics.

Research efforts will include

  • Development of reduced order models for multiphysics engineering systems
  • Development of data mining, machine learning, and optimization algorithms
  • Development of topology optimization algorithms

The preferred qualifications include:

  • Strong background in linear algebra, and computational mathematics and/or mechanics
  • Experience in developing numerical models, codes, and computation algorithms (CFD and FEM)
  • Hands-on experience with computing in Matlab, C/C++, Python, or other object-oriented programming languages
  • Strong interest and self-motivation to perform cutting-edge research and conquer challenges in real-world engineering and to publish high-impact papers

USC is the flagship university in the State of South Carolina, and the Ph.D. program at the department of Mechanical Engineering is ranked No. 31 nationally by the National Research Council (NRC) (, and the College of Engineering and Computing is ranked No. 1 in the State of South Carolina for faculty research productivity.

The group of Dr. Wang focuses on computational and data-enabled science and engineering (CDS&E) and its applications in real-world multiphysics systems, including micro/nanofluidics, energy management, additive manufacturing, aerodynamics & aerospace. CDS&E, recently emerging as a focal point of multidisciplinary research has been applied to essentially each phase of technology development and industrial engineering, from conceptualization, virtual prototyping and design, and automation and control, to final verification and validation (V&V). Our group aims to discover and develop new methodologies, framework, and capabilities to bridge CDS&E and system engineering in the real world and with particular emphasis on multiphysics and engineering intelligence. To apply, please send your CV/Resume, publications, etc. in a single PDF to Dr. Wang ( with the email subject "Position Application".

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Contact Information

  • Yi Wang
    Mechanical Engineering
    University of South Carolina
    300 Main Street
    Columbia, SC 29208

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