Meta Research Scientist Intern,AI Core Machine Learning (PhD) (Tel-Aviv) in Tel Aviv, Israel
Meta AI (FAIR), a world-class research lab, is seeking Research Interns to join our research teams to work on challenging problems that would require strong research and engineering skills to achieve a deep understanding of the problems, develop innovative approaches, and scale up with massive data and compute. Our efforts are to push the bar in the following research directions: Computer Vision, Natural Language Processing, Speech, Reinforcement Learning & Reasoning, Core Machine Learning and Creativity. We are proposing Summer, Fall, and Winter start dates. To learn more about our research, visit https://research.facebook.com.
Research Scientist Intern,AI Core Machine Learning (PhD) (Tel-Aviv) Responsibilities:
Brainstorm with research mentors, review literature and existing solutions of a challenging real-world research problem.
Develop novel solutions, implement prototypes and perform extensive experiments to test the proposed solutions in meaningful benchmarks and metrics, analyze the results and verify the conclusions.
Communicate and discuss with team members about various aspects of the project. This includes answering questions, addressing concerns, improving solutions, etc.
Draft and polish research publications.
Present research outcomes to internal and (possibly) external audiences.
Perform specific responsibilities which vary by team.
Currently has, or is in the process of obtaining a PhD degree.
Experience in Python, C++ or other related languages.
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorisation during employment
Strong publication records in specific fields (e.g., high impact research works published on top-tier conferences, popular github repositories, etc)
Intent to return to degree-program after the completion of the internship/co-op
Extensive experience solving analytical problems using quantitative approaches
Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
Ability to communicate complex research in a clear, precise, and actionable manner
Experience building large-scale machine learning systems and training with large datasets.