At a Glance
- Tasks: Conduct groundbreaking research in AI and collaborate with top academics.
- Company: Join Meta's innovative FAIR team in London, leading AI advancements.
- Benefits: Gain invaluable experience, mentorship, and access to cutting-edge resources.
- Other info: 4-year PhD position with opportunities for open science and collaboration.
- Why this job: Make a real impact in AI while working on exciting projects.
- Qualifications: Knowledge in machine learning and programming; passion for AI research.
The predicted salary is between 25000 - 32000 £ per year.
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. In London, we are specifically working on natural language processing, 3D computer vision, and reinforcement learning. For this position, we are looking for an individual passionate about furthering our understanding of large foundation models and making them safer and more accurate.
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.
Responsibilities
- Perform research to advance the science and technology of intelligent systems.
- Perform research to understand the mechanisms learned by foundation models.
- Influence progress of relevant research communities by producing publications.
- Collaborate and increase productivity on existing research projects.
Minimum Qualifications
- Knowledge in Machine Learning.
- Knowledge in a programming language.
- Must obtain work authorisation in the country of employment at the time of hire, and maintain ongoing work authorisation during employment.
- Applicants will need to separately apply and be accepted to UCL, and mention their FAIR application in the UCL application form.
Preferred Qualifications
- Bachelors or Masters degree (or equivalent) in a technical field such as Computer Science, Applied Mathematics, or equivalent practical experience.
- Experience building systems based on machine learning and/or deep learning methods.
- Research and software engineer experience demonstrated via an internship, work experience, coding competitions, or open-source contributions.
- Knowledge in Python, Lua, C++, C, C# and/or Java.
- Publications or experience in fields related to machine learning, AI, computer vision, natural language processing, computational neuroscience, optimisation, computer science, statistics, applied mathematics, or data science.
PhD Student, AI employer: Meta Platforms, Inc.
Meta is an exceptional employer for PhD students in AI, offering a unique opportunity to work at the forefront of artificial intelligence research in London. With a strong commitment to open science and collaboration with UCL, employees benefit from a vibrant work culture that fosters innovation and personal growth, alongside access to cutting-edge resources and mentorship from leading experts in the field.
StudySmarter Expert Advice🤫
We think this is how you could land PhD Student, AI
✨Tip Number 1
Network like a pro! Reach out to current PhD students or researchers in AI, especially those at Meta or UCL. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your passion! When you get the chance to interview, share your excitement about AI and how you see yourself contributing to the FAIR team. Let them know you’re all in for open science!
✨Tip Number 3
Prepare for technical questions! Brush up on your machine learning knowledge and coding skills. Practising common algorithms and programming challenges can really help you shine during interviews.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at Meta and making an impact in AI research.
We think you need these skills to ace PhD Student, AI
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for AI and machine learning shine through. We want to see how passionate you are about advancing the field and why you’re excited about joining our FAIR team.
Tailor Your CV:Make sure your CV highlights relevant experience in machine learning and programming. We’re looking for specific skills that match the job description, so don’t be shy about showcasing your projects and achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for this PhD position. Be sure to mention your research interests and how they align with our work at FAIR. We love seeing candidates who can connect their goals with our mission.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way to ensure we receive all your materials and can review them properly. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Meta Platforms, Inc.
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning and the specific areas mentioned in the job description, like natural language processing and reinforcement learning. Be ready to discuss your previous projects or research that relate to these topics.
✨Show Your Passion
Meta is looking for someone who is genuinely passionate about advancing AI. Share your enthusiasm for the field and any personal projects or contributions you've made, especially those that align with open science and open source principles.
✨Prepare for Technical Questions
Expect some technical questions during the interview. Practice coding problems in Python or any other relevant programming languages. You might also be asked to explain complex concepts in simple terms, so be prepared to demonstrate your understanding clearly.
✨Collaborative Mindset
Since this role involves collaboration with UCL, highlight any experience you have working in teams or on joint projects. Discuss how you can contribute to a collaborative environment and how you value input from others in your research.
