Raytheon Technologies Senior Research Engineer in Berkeley, California
United States of America
RCCA1: UTRC California Office 2855 Telegraph Avenue, Berkeley, CA, 94705 USA
Raytheon Technologies CorporationRaytheon 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 Systems, 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 Waltham, Massachusetts.
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.
Raytheon Technologies Research CenterThe Technology & Engineering 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.
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 senior research engineer specialized in large-scale computational mathematics and optimization.
The Optimization Team develops and deploys advanced computational mathematics and optimization methods for complex integrated system design, simulation and analysis and real time decision making under uncertainty with broad range of applications in aerospace and defense including, but not limited to, jet engines, aerospace system design, advanced manufacturing and aftermarket operations, autonomous systems, and sustainability. We support all RTX business units, including both development of novel solutions for future products and solving the toughest problems with current products.
We are looking for a highly motivated candidate eager to apply and extend the state-of-the-art large-scale computational mathematics and optimization. The candidate is expected to work on transitioning novel concepts from early technology stages to a state that impacts and influences businesses and applications. The successful candidate will
provide technical expertise in one or more of the following areas including large-scale computations and numerical methods for ODEs, DAEs and/or PDEs, discrete time/event simulations, continuous optimization, discrete optimization and graph theory, distributed optimization, uncertainty quantification and Bayesian inference, decision making under uncertainty, dynamical system analysis, and/or computational mathematics as developed on high performance computers, GPUs, and other emerging platforms such as neuromorphic/quantum computers. Of particular interest are demonstrated skills in these areas for industrial problems.
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.
Required: M.Sc. in Mathematics, Engineering, Computer Science, Operations Research or a related field
Preferred: Ph.D. in Mathematics, Engineering, Computer Science, Operations Research or a related field
The successful candidate will have expertise in one or more of the following areas: optimization, simulation and/or large-scale scientific computations and associated numerical methods. Experience with one or more is required: Python, MATLAB/Simulink, C++, CPLEX/Gurobi, CUDA. Additional expertise in one or more of the following areas is preferred: multi-disciplinary optimization, design space exploration, distributed optimization, machine learning based methods in optimization, dynamical systems, uncertainty quantification and/or graph theory.
Previous experience with industrial applications in these fields is highly desirable. The preferred candidate will have a record of innovation as evidenced by patent applications, contribution to government funded basic research programs, and/or high-quality journal and conference publications.
Additional Skills and Abilities
Strong analytical, problem-solving, and interpersonal skills with track record of teamwork, adaptability, innovation, and initiative.
Clear and effective communication with all levels of management, business development, researchers, and customers.
Ability to focus on results in a fast-paced, dynamic team environment.
Ability to work independently with limited direction and in multidisciplinary environment to accomplish project goals.
The preferred candidate will look at open-ended tough problems as an opportunity to innovate and develop novel solutions.
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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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.