南卡罗莱纳大学机械工程系王懿教授招收全奖博士研究生: 多物理系统建模，机器学习及优

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美国南卡罗莱纳大学机械工程系王懿教授招收全奖博士研究生: 多物理系统建模，机器学习及优化设计

PhD positions in Mechanical Engineering are immediately available in the research group of Dr. Yi Wang at the University of South Carolina-USC (Columbia/Main campus, https://www.sc.edu/study/college ... y-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].

[1] http://www.me.sc.edu/about/
[2] https://sc.edu/study/colleges_sc ... g/about/employment/

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 (yiwang@cec.sc.edu) with the email subject "Position Application". Detailed description for the position is:

Numerical Modeling and Machine Learning for Multiphysics Engineering Systems Design
We will investigate and develop numerical modeling and machine learning methodology and frameworks for predictive analysis and design of multiphysics systems for a variety of engineering applications, which include but not limited to microfluidics & nanofluidics, photonic integrated circuits (PIC), energy management, and additive manufacturing.

Research efforts will include
"        Development of data-driven and physics-based models for multiphysics engineering systems
"        Development of data mining and machine learning algorithms, in particular, data reduction/compression, supervised and unsupervised learning, and deep neural network (DNN)
"        Uncertainty quantification and design optimization

The required qualifications include:
"        Strong background in numerical algebra, optimization, and control theory required
"        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
"        Numerical modeling experience in one (or several) of the following systems: microfluidics & nanofluidics, thermal-fluidic systems, photonic integrated circuit, energy and battery management.
"        Experience with GPU-based computing and/or heterogeneous computing for numerical computation and deep-learning 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 papers