PhD Research Scientist Intern - Foundational Research

Interested in training and evaluating large-scale LLMs (>200B) in a frontier research team focused on AI impact in high-stakes domains? Thomson Reuters Foundational Research gives you the opportunity to research & publish on a wide range of topics in AI research while gaining experience working in a data- & compute-rich environment focused on solving real-world economically impactful problems. You will join a collaborative team that values intellectual curiosity, innovative thinking, and combines the strengths of industrial resources with an academic mindset focused on advancing science.

About the Role

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.

Responsibilities

• 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 in 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.

Benefits

• 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.
• 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.
• 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.
• 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.
• 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.

About Us

Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency.

Equal Employment Opportunity

As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law.