**Summary:** Meta is seeking a PhD Student to join its Fundamental AI Research (FAIR) team in London. We are committed to advancing the field of artificial intelligence by making fundamental advances in scientific methods and technologies to help interact with and understand our world. For this position we are looking for an individual to work at the intersection of formal verification and machine learning. Our research interest include, for example, proof assistants (e.g., Lean), automatic code analysis (e.g., abstract interpretation), code synthesis, reinforcement learning, and large language models. The remit of the PhD will be to conduct research on a problem, or problems, in these areas which is beyond what current techniques can do.PhD positions are 4-year fixed-term for PhD students in London who will work in collaboration with the UCL Centre for Artificial Intelligence, jointly supervised by academics at this lab and research scientists at FAIR. In the spirit of FAIR’s general mission, we expect the work to come out of the PhD, both at Meta and the academic partner, to be open science and open source. **Required Skills:** AI Research Assistant (PhD) Responsibilities: 1. Perform research to advance the science and technology of intelligent systems. 2. Perform research to understand the mechanisms learned by ML models. 3. Influence progress of relevant research communities by producing publications. 4. Collaborate and increase productivity on existing research projects. **Minimum Qualifications:** Minimum Qualifications: 5. Knowledge in Machine Learning. 6. Knowledge in Formal Verification. 7. Must obtain work authorisation in the country of employment at the time of hire, and maintain ongoing work authorisation during employment. 8. Applicants will need to separately apply and be accepted to UCL, and mention their FAIR application in the UCL application form. https://www.ucl.ac.uk/computer-science/study/postgraduate-research/computer-science-mphilphd **Preferred Qualifications:** Preferred Qualifications: 9. Bachelors or Masters degree (or equivalent) in a technical field such as Computer Science, Applied Mathematics, or equivalent practical experience. 10. Experience building systems based on machine learning and/or deep learning and/or formal verification methods. 11. Research and software engineer experience demonstrated via an internship, work experience, coding competitions, or open-source contributions. 12. Knowledge in Python, Lua, C++, C, C#, and/or Java 13. Publications or experience in fields related to verification, program semantics, machine learning, AI, natural language processing, optimisation, computer science, statistics, applied mathematics, or data science. **Industry:** Internet