Research Scientist in AI​/ML Dynamics and Control; Hybrid

Date posted:

Location:

US-CT-EAST HARTFORD-RTRC L ~ 411 Silver Ln ~ RTRC L

Role type:
Hybrid (onsite and offsite work)

Security clearance:
None required

Research Engineer – Learning for Dynamics and Control, Dynamics, Control, and Autonomy Team, Intelligent & Cyber‑Physical Systems Department, RTX Technology Research Center (RTRC)

• Design and develop novel control solutions for aerospace and defense applications such as jet engines, missiles, autonomous vehicles, avionics, aircraft power systems, hypersonic vehicles, advanced manufacturing, and space systems.
• Work in a multidisciplinary setting, bringing a system‑level perspective to new cutting‑edge technologies from fields such as autonomy, power systems, cyber security, mechanical systems, aerodynamics, and thermal management.
• Lead and support externally and internally sponsored programs, writing research proposals and funding applications.
• Disseminate research results through reports, conference proceedings, and peer‑reviewed articles, and develop intellectual property.

• Ph.D. in Mathematics, Physics, Computer Science, or Engineering.
• Strong fundamentals in control theory and application, including multi‑variable control and estimation techniques (e.g., LQR/LQG, Kalman filters, optimization‑based control, Model Predictive Control).
• Experience with machine learning for control, such as Reinforcement Learning for safety‑critical systems, model‑based RL, Sim2
  
  Real transfer learning, or safety guarantees using Control Barrier Functions.
• Verification & validation of AI/ML control laws and neural‑network representations of controllers and estimators.
• Control‑oriented modeling of physical systems using first‑principles and data‑driven methods, including Physics‑Informed Neural Networks.
• Proficiency in MATLAB/Simulink, Python, and deep learning frameworks such as PyTorch or Tensor Flow.

• Master’s degree in a relevant field with at least 5 years of full‑time industrial experience.
• Experience with Hardware‑in‑the‑Loop validation and real‑time/embedded implementation of control laws (Speedgoat, dSPACE, Lab View/NIDAQ).
• FPGA programming in VHDL/Verilog and C/C++ programming.
• Experience with multi‑agent collaborative autonomy, decentralized mission planning, and execution.
• Hands‑on experience implementing autonomy algorithms in high‑fidelity simulations and/or hardware platforms (PX4, Ardu Pilot, ROS/ROS2, Gazebo).
• Knowledge of open‑source planning and perception software packages and commercial UAV/UGV platforms.
• Experience in technical areas such as Neural and symbolic AI, resilient contingency management, human‑robot teaming, large language models, and agentic control.
• Prior record of writing proposals for government‑funded research, grant success, patent applications, and high‑quality journal or conference publications.
• Active security clearance (preferred).

• Strong analytical, problem‑solving, and interpersonal skills with a track record of teamwork and innovation.
• 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 and work independently with limited direction.
• Adaptability to multidisciplinary environments to accomplish project goals.

• Salary range: $86,800 – $165,200 USD (depending on experience and qualifications).
• Eligible for health, dental, vision, life insurance, short‑term and long‑term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, and parental leave.
• Potential eligibility for annual short‑term and long‑term incentive compensation programs.

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 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.