Date Posted:
2022-11-17-08:00
Country:
United States of America
Location:
RC1: United Tech Research Center 411 Silver Lane, East Hartford, CT, 06108 USA
Position Role Type:
Hybrid
Raytheon Technologies Corporation is an Aerospace and Defense company that provides advanced systems and services for commercial, military and government customers worldwide. It comprises four industry-leading businesses – Collins Aerospace, Pratt & Whitney, Raytheon Intelligence & Space and Raytheon Missiles & Defense. Its 195,000 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, Raytheon Technologies 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 Corporate or Research Center Team:
Senior Research Engineer
The Optimization Team, part of the Aerothermal and Intelligent Systems Department, at Raytheon Technologies Research Center (RTRC) is looking for a highly motivated individual for the position of research engineer specialized in the area of optimization enhanced by machine learning.
We are looking for a highly motivated candidate eager to apply and extend the state of the art in optimization enhanced by machine learning methods. The candidate is expected to work on transitioning novel concepts from early technology stages to a state that impacts and influences businesses and applications.
Responsibilities:
- Provide technical expertise in the areas of mathematical programming (linear/nonlinear/integer/stochastic programming) enhanced by machine learning methods, large-scale combinatorial optimization and distributed optimization.
- Design and develop novel optimization solutions, combined with machine learning techniques, including reinforcement learning and deep learning, to complex product and system design, and real-time decision-making problems in aerospace and defense applications including, but not limited to jet engines, missiles, autonomous vehicles and systems, advanced manufacturing, and space systems.
- Lead and support externally and internally sponsored programs, writing external and internal research proposals.
- Build relationships to support developing business relationships with industry, academia, and government agencies.
- Disseminate research results through reports, conference proceedings, and peer-reviewed articles, and developing intellectual property.
Basic Qualifications:
- Have a strong background and understanding of mathematical programming including linear programming, nonlinear programming, mixed-integer programming and derivative-free optimization techniques.
- Experience in both developing problem formulation and designing advanced algorithms for optimization problems is required, and the candidate will be able to use and combine them as appropriate to solve difficult practical problems.
- Have experience with applying machine learning techniques in context of solving large scale and real time optimization problems.
- Have software programming skills in Matlab, Python and CPLEX/Gurobi.
- Must be self-motivated
- Must have excellent written/verbal communication and strong problem-solving skills.
Preferred Qualifications:
- Experience with developing and applying state of art algorithms for large-scale combinatorial optimization, multi-disciplinary black-box optimization, stochastic optimization, distributed optimization, and/or supply chain optimization.
- Knowledge of machine learning techniques including Deep learning and graph neural networks, Reinforcement learning or Statistical Learning (e.g., Bayesian learning.)
- Exposure to SciKitLearn, PyTorch/TensorFlow.
- Experience with embedded real time optimization.
- Experience with GPUs and high-performance computing.
- Demonstrates strong understanding of science and engineering principles and a record of innovation as evidenced by patent applications, contribution to government funded basic research programs, and/or high-quality journal and conference publications.
- U. S. Citizen or Permanent Resident (Green Card) is preferred.
Location:
Two possible options are available for this role:
- East Hartford, CT (Hybrid)
***Relocation is offered only to this location.
- Berkeley, CA- If a candidate is located near this office, there is a hybrid work option.
Education:
- M. S. degree in Mathematics, Operations Research, Electrical Engineering or a relevant discipline is required.
- Ph.D. degree in Mathematics, Operations Research, Electrical engineering or a relevant discipline is highly preferred.
Typically requires:
- A University Degree or equivalent experience and minimum 5 years prior relevant experience, or An Advanced Degree in a related field and minimum 3 years' experience.
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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.
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