Reports to: Lead data scientist, Principal Investigator
Duration: up to 6 months
CSE is looking for a mid-level deep learning specialist to work on a project, “Adjusting PID Coefficients of UAV Control Using Reinforcement Learning” within the scope of the Afeyan Family Foundation grant.
Responsiabilities
Collaborating on the development and refinement of RL-based PID tuning algorithms.
Implementing and maintaining simulation environments (e.g., Gazebo, PX4) for training and testing control algorithms.
Assisting in the integration of RL models into UAV firmware, particularly ArduCopter-based systems.
Writing efficient, clean, and well-documented code for both simulation and hardware deployment.
Debugging, testing, and optimizing control algorithms in both virtual and real-world UAV environments.
Supporting data collection and analysis for performance evaluation and system improvement.
Contributing to technical documentation and preparing materials for presentations and publications.
Participating in team meetings, design discussions, and code reviews to ensure progress and alignment with research goals.
Qualifications
Must
B.S. or M.S. in Computer Science, Data Science, Robotics, Electrical Engineering, Control Systems or related field.
Strong understanding of the Reinforcement Learning Concepts or Control Systems
Strong proficiency in Python
Experience working with Git and collaborative development environments.
Experience with reinforcement learning frameworks (e.g., Stable-Baselines3, Ray RLlib, OpenAI Gym).
Ability to independently run experiments, debug models, and document findings clearly.
Nice to have:
Understanding of PID controllers and control systems theory.
Familiarity with UAV simulation environments (e.g., Gazebo, PX4, SITL).
Additional Information
Please submit your CV and Cover Letter here.
AUA is an equal-opportunity employer and is committed to an active non-discrimination program within the institution.