Intern/Thesis – Learning-based Radar-Camera Fusion for Simultaneous Localization and Mapping

This is a fully remote position, open to applicants in Germany.

📋 Description

• Conduct independent investigations into innovative methods for radar-camera integration.

• Create and assess techniques for reliable state estimation, localization, and/or 3D map creation.

• Design experiments and benchmark methods against leading-edge techniques.

• Evaluate outcomes and extract insights for multi-modal SLAM algorithms.

• Collaborate with the ground truth generation team and PhD researchers on radar-camera integration and robust SLAM research pertinent to autonomous vehicles.

• Contribute to studies on radar-camera state estimation, reliable localization, consistent map generation, and the cross-modal alignment of vision and radar data.

⛳️ Requirements

• Outstanding academic record.

• Current enrollment in Computer Science, Robotics, Electrical Engineering, Mathematics, or a related field.

• Familiarity with relevant sensors used in autonomous driving and measurement technologies.

• Proficiency in programming with experience in Python and/or C++.

• Strong command of English, both spoken and written.

• A collaborative team player with a passion for self-driving technologies and tackling challenging problems.

• Prior research experience, including internships, projects, publications, or coding competitions, is advantageous.

🏝️ Benefits

• Options for remote work within Germany.

• Flexible remote working arrangements based on mutual agreement.

• Support for diversity and inclusion initiatives.

• Assistance with applications for candidates with disabilities.