Aerospace Engineering Intern (UNPAID)

Graduate Robotics / Aerospace Engineering (UNPAID Intern) – Drone Dynamics & ControlJob DescriptionEmbark on an exciting startup journey and contribute to cutting-edge research in autonomous aerial robotics! We are offering an unpaid internship opportunity for highly motivated graduate students interested in dynamics modeling, control systems, and autonomous drone navigation.Join our team as we develop advanced algorithms enabling an autonomous aerial drone to land on a moving base platform. This challenging problem combines robotics, aerospace dynamics, estimation, and optimal control, offering a unique opportunity to work on real-world autonomous systems.You will collaborate with a multidisciplinary team currently developing the hardware, electronics, and platform infrastructure, while focusing specifically on the software and control algorithms required to perform precision landing maneuvers.This internship is ideal for students passionate about robotics, aerospace engineering, control theory, and autonomous systems who want hands-on experience tackling real-world autonomy challenges.ResponsibilitiesDynamic Modeling: Develop mathematical models of the drone and landing platform dynamics to support simulation and control development.Control Algorithm Development: Design and implement control strategies enabling the drone to safely land on a moving base. Approaches may include optimal control, model predictive control, adaptive control, or other advanced techniques.State Estimation: Implement estimation algorithms such as Kalman Filters or sensor fusion methods to accurately estimate vehicle state during flight and landing maneuvers.Simulation and Testing: Build and run simulations to validate control strategies before real-world deployment. Work with the hardware team to test algorithms on the physical platform.Software Development: Implement control and estimation algorithms using languages and tools commonly used in robotics (such as Python, C++, MATLAB).RequirementsEducation: Currently pursuing a graduate degree in Aerospace Engineering, Robotics, Mechanical Engineering, Electrical Engineering, or a related field.Control Systems Knowledge: Background in control theory, dynamic systems, and state estimation techniques.Programming Skills: Experience with Python, C++, or MATLABModeling & Simulation: Experience with system modeling, simulation environments, or control system implementation.Location: Live in Daytona Beach or surrounding locations, as this is an on-site position.Mindset: Strong curiosity, problem-solving skills, and willingness to explore advanced control methods.