Date Posted:
2023-11-03
Country:
United States of America
Location:
RC1: United Tech Research Center 411 Silver Lane, East Hartford, CT, 06108 USA
Position Role Type:
Hybrid
RTX Corporation is an Aerospace and Defense company that provides advanced systems and services for commercial, military and government customers worldwide. It comprises three industry-leading businesses – Collins Aerospace Systems, Pratt & Whitney, and Raytheon. Its 185,000 employees enable the company to operate at the edge of known science as they imagine and deliver solutions that push the boundaries in quantum physics, electric propulsion, directed energy, hypersonics, avionics and cybersecurity. The company, formed in 2020 through the combination of Raytheon Company and the United Technologies Corporation aerospace businesses, is headquartered in Arlington, VA.
To realize our full potential, RTX is committed to creating a company where all employees are respected, valued and supported in the pursuit of their goals. We know companies that embrace diversity in all its forms not only deliver stronger business results, but also become a force for good, fueling stronger business performance and greater opportunity for employees, partners, investors and communities to succeed.
The following position is to join our RTX Corporate, Enterprise Services, Research Center or BBN team:
The Technology & Global Engineering (T&GE) organization is comprised of the global engineering function, several focused centers of expertise, and our advanced Research & Development Facility – the Research Center. By combining a passion for science with precision engineering, we create smart, sustainable solutions that prove we can do the big things the right way.
RTRC’s aerodynamics and acoustics discipline encompasses a critical mass of numerical simulation and design optimization capabilities and experimental facilities to develop novel and innovative technologies for advanced propulsion and aircraft systems, including high-speed flight vehicles.
Role Overview
The Summer 2024 Fluid Dynamics Data Scientist Intern will be responsible for one or more of the following activities:
- Establish, implement, and validate machine learning approaches for modeling augmentation in Reynolds Averaged Navier Stokes (RANS) and Large Eddy Simulation (LES), in the context of film cooling in gas turbines and boundary layer development on hypersonic vehicles.
- Embed physics-based constraints in deep learning architectures for control and/or material characterization in the context of conjugate heat transfer.
- Work closely with cross-functional research teams to leverage real-world data for machine learning training and validation of modeling augmentation against experiments.
- Present research accomplishments in the form of presentations and written publications.
Required Qualifications
Candidates should have an elaborate understanding of machine learning opportunities in physical sciences to support new aero-thermal research. Experience with Large Eddy Simulation is desired. Candidates must be able to work effectively in a multidisciplinary, collaborative team environment focused on innovation and possess a variety of skills including:
- Presentation, planning, problem solving, project management and decision-making skills
- Advanced machine learning skills, including deep learning architectures
- Experience with Computational Fluid Dynamics (CFD) methods and applications
Education
Candidates must be enrolled in a Master's degree or Ph.D. degree program in the field of Aerospace, Mechanical Engineering or related technical field. A minimum 3.5 GPA is required. Please upload unofficial transcript with your application.
Work Authorization
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U.S. Person (U.S. citizen or permanent resident) or eligible to obtain necessary export authorizations required.
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Job location:
Remote with optional on-site presence in East Hartford, CT.
RTX 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.
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