[ME/AERO] 美国马萨诸塞大学机械系 全奖 招收 计算流体力学，航空声学方面的博士生2名

cychuliUID: 3542863

UMass Lowell机械工程系的Assoc Prof David Willis招收Aero-acoustics, computational fluid dynamics方向的博士生两名，全奖资助（含学杂费tuition and fees，生活费stipend 和 health insurance）。
职位描述请见下文。
来校时间越快越好，有相应背景的同学请尽快联系。春季开学也来得及的哦！可直接发电子邮件到 David_Willis@uml.edu，附上a short CV/Resume and a short statement highlighting your interest and experience.

PhD Assistantship Opening # 1:  Computational Aero-Acoustics (CAA)
Type of position: PhD Thesis
Support: 50% RA (NSF), 50% TA
Project Duration: ~3 years
Funding: NSF Funded, Competitive Stipend

The researcher in this position will develop and use computational aero-acoustics simulation tools to perform  CAA simulations/predictions. Coupled fluid-acoustic and/or high-fidelity predictive tools for aero-acoustics prediction will be considered/developed/used in this research.

The ideal candidate will have a strong interest in scientific computing, aerodynamics and/or aero-acoustics. Background/experience in computer programming using compiled languages (Fortran, C, C++, other) and numerical methods for PDEs (boundary/finite element, finite difference and/or finite volume) and/or prior experience using CFD/CAA tools is strongly preferred. Parallel computing experience is advantageous, but not required.



PhD Assistantship Opening # 2:  Computational Fluid Structure Interaction
Type of position: PhD Thesis
Support: 100% RA
Project Duration: ~3 years
Funding: NSF Funded

The researcher in this position will develop and use computational tools to assess problems with strong fluid structure interaction in low Reynolds number aerodynamics flows. Low-fidelity 'computational aerodynamics' tools and/or higher fidelity CFD tools may be  considered, developed and/or used.

The ideal candidate will have a strong interest in scientific computing, aerodynamics and/or aero-elasticity. Background/experience in computer programming (Fortran, C, C++, other) and numerical methods for PDEs (boundary element and/or DG-FEM) and/or prior experience using CFD/FSI tools is strongly preferred. Parallel computing experience is advantageous, but not required.


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David J. Willis
Associate Professor of Mechanical Engineering
University of Massachusetts Lowell
(978)934-3101
David_Willis@uml.edu
http://faculty.uml.edu/dwillis/

du_congUID: 3617664

昌昌你好  

pielangUID: 3284254

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