Post-Doctoral Associate in the Center for Artificial Intelligence and Robotics (CAIR) - Dr. Farshad Khorrami

The Center for Artificial Intelligence and Robotics (CAIR) at NYU Abu Dhabi invites qualified applicants with a doctorate degree in the areas of electrical or computer engineering or computer science, or related fields to apply. A strong publication record is encouraged and previous experience in areas such as Neural network vulnerabilities and defenses, Anomaly detection, Adversarial machine learning, Computer vision, and Autonomous Robots is desired.

The successful applicant will work on various projects on robotics and computer vision, controls, and machine learning and their security. The work will include algorithm design, prototype implementation (e.g., in MATLAB/Python), deployment to robotics applications; onboard computational hardware using the Robot Operating System), and experimental testing (on unmanned vehicle swarms). A solid competency with the standard implementation tools used in machine learning and embedded systems (e.g., C, C++, Linux, PyTorch, TensorFlow, MATLAB, Python, Robot Operating System) is required.

The position is open to PhDs with backgrounds in AI, and/or computer vision and robotics/controls, and with less than 5 years of experience after receiving their PhD. The candidate is expected to work in a highly collaborative multi-disciplinary environment with other post-doctoral associates, PhD and undergraduate students, as well as faculty members (both in NYU Abu Dhabi and NYU New York). It is expected that applicants have a strong publication record in the aforementioned areas. The applicants are also expected to have strong analytical, communication, and writing skills.

Applications will be accepted on a rolling basis and candidates will be considered until the positions are filled. To be considered, all applicants must submit a cover letter, curriculum vitae, transcript of degree/ copy of highest degree, research statement, and at least 2 contact references referees having essential knowledge of the candidate’s academic work, all in PDF format.

If you have any questions, please reach out to Dr. Farshad Khorrami at khorrami@nyu.edu.