Intern - FCS

About the Role:

Key Responsibilities:

• Flight Dynamics and Control: Assist in the design, analysis, and tuning of control algorithms (e.g., PID, LQR, model predictive control) for stable and responsive flight control, considering flight dynamics principles.
• ML/AI Integration: Support the use of machine learning models and AI techniques for adaptive control, predictive maintenance, fault detection, and system optimization.
• Vision-Based Control: Develop and implement vision-based control strategies using computer vision and image processing algorithms for navigation, landing, obstacle avoidance, GPS denied navigation and target tracking.
• Flight Simulation: Conduct simulations of flight dynamics and control systems using MATLAB/Simulink or similar tools, incorporating both traditional control methods and ML/AI-enhanced approaches.
• Sensor Fusion & Data Integration: Combine data from various sensors (e.g., cameras, LiDAR, IMUs) to enhance flight control systems and improve vehicle performance in complex environments.
• Data Analysis: Analyze flight and sensor data to tune control parameters, using machine learning for anomaly detection, pattern recognition, and performance enhancement.
• Embedded Systems: Work on the implementation of control algorithms in embedded systems, including the deployment of AI/ML models for real-time control and decision-making.
• Research and Development: Conduct research on advanced guidance, navigation, and control (GNC) strategies using flight dynamics, AI/ML, and vision-based technologies to enhance the autonomy of aerospace vehicles.
• Documentation: Prepare technical reports and document flight control designs, test plans, and simulation results for review.

Required Qualifications:

• Currently pursuing a Bachelor’s or Master’s degree in Aerospace Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
• Strong interest and understanding of flight dynamics, control theory, and vehicle aerodynamics.
• Experience with MATLAB/Simulink for modeling and simulation of dynamic systems and control design.
• Basic knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and computer vision (OpenCV).
• Familiarity with programming languages such as Python, C/C++ for control algorithm development and AI/ML model implementation.
• Interest in UAVs, aircraft systems, and/or spacecraft control systems.
• Analytical problem-solving skills with attention to detail.

Preferred Qualifications:

• Experience with aerospace control systems such as PX4, ArduPilot.
• Knowledge of flight dynamics modeling and simulation tools such as X-Plane, Gazebo, or FlightGear.
• Familiarity with vision-based navigation, SLAM (Simultaneous Localization and Mapping), and sensor fusion techniques.
• Experience with hardware-in-the-loop (HIL) testing, real-time simulations, or flight testing environments.
• Understanding of AI techniques like reinforcement learning, neural networks, or decision-making algorithms for control.
• Knowledge of ROS (Robot Operating System) for integrating control systems and AI/ML algorithms.
• Experience with real-time operating systems (RTOS) and embedded software development.

What You Will Gain:

• Hands-on experience in flight dynamics, control system design, and integration of ML/AI technologies in aerospace applications.
• Exposure to state-of-the-art simulation tools, control systems, and autonomous flight technologies.
• Collaboration with professionals in GNC, AI, and vision-based system development, gaining insights into both classical and modern control methods.
• Practical experience in hardware-in-the-loop testing, sensor fusion, and flight control optimization.
• Networking opportunities in the aerospace and AI industries, with potential pathways for future career growth.

This internship supports the development and testing of control systems and autonomy technologies for UAVs and other aerospace vehicles. The work spans flight dynamics, simulation, computer vision, sensor data, and AI/ML methods, alongside embedded implementation and technical documentation.

Role at a glance

Skills mentioned

What you will likely work on

• Assist with designing, analyzing, and tuning flight-control algorithms using flight-dynamics principles.
• Support AI/ML approaches for adaptive control, predictive maintenance, fault detection, and system optimization.
• Develop vision-based navigation and control for landing, obstacle avoidance, GPS-denied navigation, and tracking.
• Simulate control systems and flight dynamics using MATLAB/Simulink or comparable tools.
• Integrate camera, LiDAR, and IMU data to support control in complex environments.
• Analyze flight and sensor data to tune controls and identify anomalies or performance patterns.
• Help deploy control algorithms and AI/ML models on embedded systems for real-time use.
• Research guidance, navigation, and control strategies, and document designs, test plans, and simulation results.

Good fit signals

• Currently pursuing a bachelor's or master's degree in a relevant engineering or computing field is required.
• The role calls for a strong interest and understanding of flight dynamics, control theory, and vehicle aerodynamics.
• Experience with MATLAB/Simulink for dynamic-system modeling, simulation, and control design is required.
• Basic knowledge of machine-learning frameworks and computer vision is sought; Python, C, or C++ familiarity is also relevant.
• Interest in UAVs, aircraft, or spacecraft systems and careful analytical problem-solving align with the stated qualifications.