Imagine New Horizons
As a Fluids Machine Learning Intern, you will conduct research in applying machine learning techniques to improve solutions for Navier-Stokes (Finite-Volume) and Lattice Boltzmann solver technologies commonly used in Computational Fluid Dynamics.
You will work with our Fluids solver developers to design and prototype methods in one or more of the following topics:
Using CFD solutions to train a neural network for performing and accelerating the solution for complex flows
Tuning turbulence models and exploring the algorithmic design space (Lattice Boltzmann or Navier-Stokes) for complex flows
Using machine learning techniques to guide the convergence of linear solvers, or to pick the appropriate linear solver for each equation to be solver and tune their paired parameters to set intelligent defaults
Training a neural network for high-fidelity for turbulence generation
Determining reduced order models through machine learning for certain classes of components like HVAC ducting, heatsinks, fans etc.
This is a 6-month, full time, 40 hours per week paid internship/co-op, January - June 2019 . This internship is based at the Dassault Systemes Simulia Corp office located on 1301 Atwood Avenue, Suite 101W, Johnston, RI 02919.
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What will Your Role Be?
Developing machine learning methodologies to accelerate our fluids solvers, improve turbulence models, and/or develop reduced order models.
Prototyping code in either Python or C++ environment for the developed methods
Verifying, calibrating and validating against available data in the literature by running various simulations
Documenting the work performed in PowerPoint and producing one final report that may result in publication (conference/journal).
Your Key Success Factors
Actively enrolled in a Master's or PhD program for the duration of the internship
Minimum of MS in Computer Science or Engineering with a focus on machine learning techniques
Demonstrate strong experience in ML frameworks like TensorFlow or Torch
Exposure to setting up and solving CFD problems commonly used in industry
Highly desirable: experience with Lattice Boltzmann and/or linear system solvers used in CFD
Demonstrates Strong skills in programming C++ and/or Python
Ability to take direction and guidance from others, can work independently
Fluency in English, both verbally and in writing
Possess strong mathematical and analytical skills
In order to provide equal employment and advancement opportunities to all individuals, employment decisions at 3DS are based on merit, qualifications and abilities. 3DS is committed to a policy of non-discrimination and equal opportunity for all employees and qualified applicants without regard to race, color, religion, gender, sex (including pregnancy, childbirth or medical or common conditions related to pregnancy or childbirth), sexual orientation, gender identity, gender expression, marital status, familial status, national origin, ancestry, age (40 and above), disability, veteran status, military service, application for military service, genetic information, receipt of free medical care, or any other characteristic protected under applicable law. 3DS will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.
3DS Dassault Systems