Research Scientist in AI/ML for Dynamics and Control (Hybrid)

Location US-CT-EAST HARTFORD-RTRC L ~ 411 Silver Ln ~ RTRC L Date Posted 2026-06-18 Country United States of America Role Type Hybrid Citizenship Requirement U.S. citizenship is required. Security Clearance None/Not Required Overview The Dynamics, Control, and Autonomy Team at RTX Technology Research Center (RTRC) is seeking a research engineer specialized in Learning for Dynamics and Control. What You Will Do Design and develop novel control solutions for aerospace and defense applications including jet engines, missiles, autonomous vehicles and systems, avionics, aircraft power systems and air management, hypersonic vehicles, advanced manufacturing, and space systems. Work in a multidisciplinary setting, bringing a system-level perspective to new cutting‑edge technologies from multiple fields (autonomy, power systems, cyber security, mechanical systems, aerodynamics, thermal management). Lead and support externally and internally sponsored programs; write external and internal research proposals. Disseminate research results through reports, conference proceedings, peer‑reviewed articles, and develop intellectual property. What You Will Learn How to transition novel concepts from early technology stages to a state that impacts and influences products with global societal impact. How to build relationships within the company and externally with industry, academia, and government agencies for long‑term impact. Qualifications You Must Have Ph.D. in Mathematics, Physics, Computer Science or Engineering. Strong fundamentals in control: standard multivariable control and estimation techniques (e.g., LQR/LQG, Kalman filters, optimization‑based control, including Model Predictive Control), from problem formulation to implementation in software. Experience with machine learning for control, including: reinforcement learning (RL) for safety‑critical systems (e.g., model‑based RL, Sim2Real transfer learning, or safety guarantees using Control Barrier Functions), verification & validation of AI/ML control laws, neural‑network representations of controllers and estimators (e.g., Physics‑Informed Neural Networks for MPC, or Neural‑Network based MPC). Control‑oriented modeling of physical systems, both from first principles and data‑driven (including learning‑based methods such as Physics‑Informed Neural Networks). Proficiency in MATLAB/Simulink, Python, PyTorch or TensorFlow. Qualifications We Prefer Master’s degree in Mathematics, Physics, Computer Science or Engineering with minimum 5 years of full‑time industrial experience. Novel approaches for safety including Control Barrier Functions (CBF). Hardware‑in‑the‑Loop validation and real‑time/embedded implementation of control laws: experience with Speedgoat, dSPACE, or LabView/NIDAQ; FPGA programming; C/C++ programming. Experience with multi‑agent collaborative autonomy, including multi‑agent autonomous behaviors, decentralized mission planning and execution. Hands‑on experience with implementation of autonomy algorithms in high‑fidelity simulations and/or hardware platforms: PX4 or ArduPilot autopilots and software‑in‑the‑loop simulations, Robot Operating System (ROS, ROS2) and Gazebo simulation, open‑source planning and perception software packages, commercial UAV and UGV platforms. Experience with one or more of the following technical areas: neural and symbolic AI approaches for course of action development; resilient contingency management for multi‑agent autonomous systems; human‑robot teaming. Application experience in one or more of the following: manufacturing and inspection operations; autonomous systems, including assurance for autonomy; safety and certification in aerospace; gas turbine engine modeling and control; guidance, navigation, and control (aircraft, spacecraft, or missiles); hypersonic propulsion; electric or hybrid‑electric propulsion for aircraft; control co‑design. Experience with Large Language Models and agentic control. Experience with writing proposals for government‑funded research, record of grants; a record of innovation as evidenced by patent applications, high‑quality journal and conference publications. Active Security Clearance. Additional Skills And Abilities Strong analytical, problem‑solving and interpersonal skills with a track record of teamwork, adaptability, innovation and initiative. Clear and effective communication at 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 multidiscipline environments to accomplish project goals. The preferred candidate will look at open‑ended tough problems as an opportunity to innovate and develop novel solutions. Compensation Salary range: 86,800 USD – 165,200 USD (good faith estimate representative of all experience levels). Benefits Medical, dental, vision, life insurance, short‑term disability, long‑term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, holidays. Annual short‑term and/or long‑term incentive compensation programs (dependent on level and collective‑bargaining status). Benefits are location‑ and business‑unit‑specific and may be affected by collective‑bargaining agreement. Equal Employment Opportunity RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act. #J-18808-Ljbffr RTX