United States of America
RC1: United Tech Research Center 411 Silver Lane, East Hartford,
CT, 06108 USA
The Aero & Acoustics Discipline team at Raytheon Technologies
Research Center is searching for a student intern familiar with
machine learning applied to physical sciences in support of new
aero-thermal research. Our team is focused on developing new and
innovative solutions to enhance the efficiency, operability, and
durability of a wide range of aerospace and defense products. The
primary responsibility of this role is to support the design and
implementation of data-driven and physics-informed neural networks.
The intern will work closely with the team to design, implement,
and demonstrate deep neural networks to augment predictive
capabilities in fluid dynamics.
+ Design, implement, and evaluate deep neural network
architectures for aero-thermal applications
+ Work closely with cross-functional research teams to evaluate
the effectiveness of predictive capability
+ Present research accomplishments in the form of a
demonstration and written publication
+ Preferred candidate is actively pursuing an advanced degree
(Master's or PHD) in an applicable discipline. A minimum GPA of 3.0
+ Must be a U.S. Person
+ Mechanical or Aerospace Engineering is highly preferred
+ Self-motivated with high energy
+ Excellent communication skills
Raytheon Technologies is An Equal Opportunity/Affirmative Action
Employer. All qualified applicants will receive consideration for
employment without regard to race, color, religion, sex, sexual
orientation, gender identity, national origin, disability or
veteran status, age or any other federally protected class.
Click on this link
(http://www.rtx.com/privacy/Job-Applicant-Privacy-Notice) to read
the Policy and Terms
Raytheon is an Equal Opportunity/Affirmative Action employer.
All qualified applicants will receive consideration for employment
without regard to race, age, color, religion, creed, sex, sexual
orientation, gender identity, national origin, disability, or
protected Veteran status.