Research of Al platforms and methods for robotic perception: the candidate will explore novel hardware and software platforms to combine model-based and machine learning techniques for robot perception (motion estimation, 3D reconstruction, SLAM, signal conversion, foundation models, etc.) with event cameras. The work combines the disciplines of robotics and optimization. Teaching duties are carried out.

• Successfully completed university degree (Master, Diplom or equivalent) in Computer Science or
  related engineering field
• Excellent knowledge and experience in machine learning, state estimation, robotic hardware and event cameras
• Programming experience with C++ and Python. Knowledge of the deep learning framework PyTorch, the robot operating system ROS, and experience in event camera data acquisition
• Publications in high-impact conferences on event cameras (such as ECCV, ICCV, CVPR) are a plus
• The ability to teach in German and/or English is required; willingness to acquire any language skills that are currently lacking

For more information, please contact Prof. Guillermo Gallego at office@rip.tu-berlin.de.

Please send your application preferably in English including the reference number and supporting documents as one single PDF file to office@rip.tu-berlin.de.

• Cover Letter with your interest and experience related to the position (1 page).
• CV Please provide your nationality (for visa purposes), date of birth, university
  affiliation, relevant skills, academic publications, awards, research videos and/or codes, and profiles on job boards.
• Bachelor's and Master's degrees and transcripts. Specify your GPA (e.g. 3.8/4.0)
• Any relevant co-authored event-camera publications.

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.