At a Glance
- Tasks: Innovate and develop cutting-edge ML/NLP solutions while publishing high-quality research.
- Company: Join Thomson Reuters, a leader in AI research with a collaborative culture.
- Benefits: Competitive pay, flexible work, mentorship, and access to vast datasets.
- Other info: Flexible hybrid work model and opportunities for career growth and social impact.
- Why this job: Make a real-world impact in AI while learning from top experts in the field.
- Qualifications: PhD student or recent graduate with research experience and strong communication skills.
The predicted salary is between 500 - 1500 £ per month.
We are seeking PhD Research Scientist Interns with flexible starting dates throughout the year in our London, Toronto & Zug locations. During your internship, you will focus on publishing high-quality research in top venues for Machine Learning & NLP while advancing our internal model development. We also value our deep academic connections, are open to involving academic advisors & collaborators.
Foundational Research is the dedicated core Machine Learning research division of Thomson Reuters. We are focused on research and development, with a particular focus on advanced algorithms and training techniques for Large Language Models (LLMs). We are building a strong foundation of research capabilities across different areas and are looking for interns who participate in designing, coding, conducting experiments, translating findings into concrete deliverables and engaging with the academic community.
Our focus areas are:
- LLM Training (Continued Pretraining, Instruction Tuning, Reinforcement Learning Algorithms & Infrastructure, Alignment, Distributed Training, ...)
- Post-training techniques for planning & reasoning (e.g. Agentic pipelines & tool use, LLMs & Knowledge Graphs, Self-reflection & critique, CoT & Reasoning, RAG, ...)
- Data-centric Machine Learning (Synthetic & Hybrid Data generation, Curriculum Learning, learned data-mixtures, ...)
- Evaluation (Benchmark design, Red-teaming/Adversarial Testing, Hallucination detection & Factuality, Human-in-the-loop testing, ...)
We work collaboratively with academic partners at world-leading research institutions (such as our joint academic lab with Imperial College London) and subject matter experts with decades of experience. We experiment, prototype, test, and deliver ideas in the pursuit of smarter and more valuable models trained on an unprecedented wealth of data and powered by state-of-the-art technical infrastructure. Through our unique institutional experience, we have access to an unprecedented number of subject matter experts involved in data collection, testing, and evaluation of trained models.
As a Research Scientist Intern, you will work alongside and learn from a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company’s leading internal AI model development. You will have the opportunity to publish your research findings as well as contribute to our proprietary AI model research & development. Thomson Reuters is known for consistently delivering successful data-driven ML solutions in pursuit of academic excellence and support of high-growth products that serve Thomson Reuters customers in new and exciting ways.
The internship duration at Thomson Reuters Labs is typically 4 to 6 months and may be aligned with one or two academic semesters or depending upon your availability.
About the Role
In this opportunity, as a PhD Research Scientist Intern you will:
- Innovate: You will have the opportunity to innovate and create new state-of-the-art ML/NLP/IR/GenAI approaches at the cutting edge of AI research. You will work closely with a Research Scientist to contribute ideas and work on solving real-world challenges using a wealth of data.
- Experiment and Develop: You are involved in the entire research & model development lifecycle, brainstorming, coding, testing, and delivering high-quality reports at leading international academic conferences.
- Collaborate: Working on a collaborative global team of researchers & engineers both within Thomson Reuters and our academic partners at world-leading universities.
- Communicate: Actively engage in sharing our technical findings with the wider community through contributions to seminars, lectures, conferences and/or the sharing of publications and/or technical assets (data & models).
About You
You’re a fit for the role if your background includes:
- PhD student or recent graduate with research experience in a relevant discipline.
- Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, ICLR).
- Familiarity with a deep learning framework (e.g. pytorch, jax, tensorflow, ...)
- Excellent communication skills to report and present research findings and developments clearly, both orally and in writing.
- Curious and innovative disposition capable of devising novel, well-founded algorithmic solutions to relevant problems.
Preferred qualifications:
- Experience working on at least one relevant state-of-the-art research topic (see our focus areas) in large language models (LLMs).
- Influential first author publications top-tier venues.
- Impactful open-source contributions.
- Strong software and/or infrastructure engineering skills with supporting evidence.
- Experience training large-scale models over distributed nodes with cloud tools such as Amazon AWS, MS Azure, or Google Cloud.
You will enjoy:
- Learning and development: On-the-job coaching, mentorship and learning from a world-leading researcher as well as the opportunity to work with cutting-edge methods and technologies.
- Plenty of data, compute, and high-impact problems: Our interns get to explore large datasets and discover new capabilities and insights. Thomson Reuters is best known for the globally respected Reuters News agency, but our company is also the leading source of information for legal, corporate, and tax & accounting professionals. We have over 60,000 TBs worth of legal, regulatory, news, and tax data. We also provide access to all major cloud computing platforms to our researchers and engineers.
- Competitive compensation: The opportunity to earn while learning new skills.
Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.
Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
PhD Research Scientist Intern - Foundational Research employer: Refinitiv
Contact Detail:
Refinitiv Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land PhD Research Scientist Intern - Foundational Research
✨Tip Number 1
Network like a pro! Reach out to current or former interns and employees on LinkedIn. Ask them about their experiences and any tips they might have for landing the role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for interviews by diving deep into the latest research in Machine Learning and NLP. Be ready to discuss your own work and how it relates to what Thomson Reuters is doing. Show them you’re not just a candidate, but a passionate researcher!
✨Tip Number 3
Don’t underestimate the power of a strong online presence. Share your research findings, engage with the academic community, and showcase your projects on platforms like GitHub or personal blogs. This can set you apart from other candidates!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Thomson Reuters team. Let’s get you that internship!
We think you need these skills to ace PhD Research Scientist Intern - Foundational Research
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your research experience and relevant skills in Machine Learning and NLP. We want to see how your background aligns with our focus areas, so don’t hold back on showcasing your publications and projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're excited about the PhD Research Scientist Intern role and how you can contribute to our foundational research. Be genuine and let your passion for AI research come through.
Showcase Your Communication Skills: Since communication is key in our collaborative environment, make sure to demonstrate your ability to convey complex ideas clearly in your application. Whether it's through your writing style or examples of past presentations, we want to see that you can engage with both technical and non-technical audiences.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Refinitiv
✨Know Your Research Inside Out
Before the interview, make sure you can discuss your research in detail. Be prepared to explain your methodologies, findings, and how they relate to the focus areas mentioned in the job description, like LLM training or data-centric machine learning.
✨Showcase Your Publications
Bring copies of your publications or have them easily accessible online. Be ready to discuss the impact of your work and how it aligns with the company's goals. Highlight any first-author papers in top-tier conferences, as this will demonstrate your capability and experience.
✨Familiarise Yourself with Their Work
Research Thomson Reuters' recent projects and publications in ML/NLP. Understanding their current focus will help you ask insightful questions and show that you're genuinely interested in contributing to their work.
✨Prepare for Technical Questions
Expect technical questions related to deep learning frameworks and algorithms. Brush up on your knowledge of tools like PyTorch or TensorFlow, and be ready to discuss your experience with distributed training and cloud platforms like AWS or Google Cloud.