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Job Record #15502
TitleReduced Order Modeling and Data Analytics for Engineering
CategoryPhD Studentship
EmployerUniversity of South Carolina
LocationUnited States, South Carolina, Columbia
InternationalYes, international applications are welcome
Closure DateWednesday, May 01, 2019
PhD positions in Mechanical Engineering are available in Fall 2019 within 
the research group of Dr. Yi Wang at the University of South Carolina-USC 
(Columbia/Main campus,
staff/yi_wang.php). 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) [1], and 
the College of Engineering and Computing is ranked No. 1 in the State of 
South Carolina for faculty research productivity [2]. 


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.

We are looking for highly motivated applicants in applied math, mechanical 
engineering, aerospace engineering, civil engineering, electrical 
engineering, or chemical engineering with strong background and experience 
in numerical modeling and high-performance computing (CFD and FEM), machine 
learning, data mining, and system control in aerospace, energy and additive 
manufacturing systems, microfluidic and nanofluidic systems, etc. 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 
( with the email subject “Position Application”. Detailed 
description for the position is: 

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

Research efforts will include 
•	Development of reduced order models for multiphysics engineering 
•	Development of data mining and machine learning algorithms, in 
particular, data reduction/compression, supervised and unsupervised 
learning, and deep neural network (DNN)
•	Design optimization

The required qualifications include: 
•	Strong background in numerical algebra and computational mathematics 
•	Experience in developing in-house numerical models, codes, and 
computation algorithms for various linear and nonlinear dynamical systems. 

The desired qualifications include: 
•	Strong hands-on experience with parallel computing and optimization 
for numerical models, data analytics, and machine learning within Matlab, 
C/C++, Python, or other object-oriented programming languages
•	Knowledge on system control and GPU computing is a significant plus
•	Strong interest and self-motivation to perform cutting-edge research 
and conquer challenges in real-world engineering and to publish high-impact 

Contact Information:
Please mention the CFD Jobs Database, record #15502 when responding to this ad.
NameYi Wang
Email ApplicationYes
Address300 Main Street
Mechanical Engineering, University of South Carolina
Record Data:
Last Modified04:54:42, Monday, December 03, 2018

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