Job ID: 142380

Ph.D. and Post-doc Position in Computing, Machine Learning, and System Control on Edge Computing

University of South Carolina

  • Jun. 1, 2020
 
  • Ph.D. and Post-doc Position in Computing, Machine Learning, and System Control on Edge Computing
  • Mechanical Engineering
  • https://sc.edu/study/colleges_school...
  • University of South Carolina
    Columbia, SC
 
  • May 31, 2021
  • Aug. 16, 2020
  •  
 
  • Graduate Student
    Post-Doc
  • Water Resources Engineering
    Transportation Engineering
    Sustainable Engineering
    Structural Engineering
    Robotics
    Optics & Optical Engineering
    Ocean Engineering
    Nuclear
    Naval Architecture & Marine Engineering
    Mechatronics
    Mechanical Engineering
    Material/Metallurgy
    Manufacturing & Quality Engineering
    Industrial & Systems Engineering
    Engineering Physics
    Engineering Mechanics
    Energy Technology
    Electrical and/or Electronics
    Computer Engineering
    Civil Engineering
    Bioengineering (all Bio-related fields)
    Aerospace/Aeronautical/Astronautics
    Engineering - Other
 
 

Multiple PhD positions with full graduate research assistantship (GRA) and post-doc 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, https://yiwangusc.wixsite.com/yiwang).

Computing, Machine Learning, and System Control on Edge Computing
We will investigate and develop control framework, algorithms, and cyberphysical systems for a variety of engineering applications on edge computing platforms, which include but not limited to energy auditing & cybersecurity, multi-fidelity model optimization, railroad and grade crossing surveillance and monitoring, and autonomous systems (real-time fault detection & mitigation, path planning, and control).

Research efforts will include at least one of the followings

  • Development of data mining, computer vision, machine learning, and optimization algorithms
  • Development of CPU+GPU computing algorithms
  • Development of control framework for various robotic platforms

At least one of the qualifications below is preferred:

  • Strong background in control theory, linear algebra, computer vision, and computational mathematics and/or mechanics
  • Hands-on experience with computing in Matlab, C/C++, Python, or other object-oriented programming languages
  • Hands-on experience with embedded system and edge-computing modules, such as Jetson TX series, Intel NUC, Raspberry Pi, and Arduino.
  • 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) (http://www.me.sc.edu/about/), 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 (for Ph.D. applicants, transcripts, and GRE scores are also required) to Dr. Wang (yiwang@cec.sc.edu) with the email subject "Position Application".


 
Please reference AcademicKeys.com in your cover letter when
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Contact Information

 
  • Yi Wang
    Mechanical Engineering
    University of South Carolina
    300 Main Street
    Columbia, SC 29208
  •  
  • yi.wang16@yahoo.com


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