Join our Data Science team to work on a hands‑on research project at the intersection of large language models (LLMs), knowledge graphs, and scientific information retrieval. You'll apply AI to real problems across chemistry, life sciences, and biomedical content, and help improve the products researchers use every day.
What you'll work on
- Grounding LLMs in domain knowledge: combining LLMs with ontologies, knowledge bases, and knowledge graphs to make outputs more accurate and reliable.
- Information extraction and entity recognition: identifying, resolving, and linking scientific entities (such as chemicals, drugs, and diseases) in text and queries.
- Search and retrieval: improving how natural-language questions become precise search queries, and how ranking signals are combined.
- Model adaptation: fine-tuning or continued pre-training of small and medium language models for scientific use cases.
- LLM engineering and evaluation: prompt design, handling large structured data such as tables, and quality-control layers for AI predictions.
What you'll do
- Review current research and define a focused research question
- Design, build, and prototype methods using LLMs and related techniques
- Run experiments and benchmark against strong baselines on real or public datasets
- Share your findings in a written report or thesis and a final presentation
Requirements
- Student in Computer Science, AI, Data Science, Computational Linguistics, Bioinformatics, Cheminformatics, or a related field
- Strong Python skills and experience with ML/NLP frameworks (e.g., PyTorch, Hugging Face)
- Familiarity with LLMs, NLP, or information retrieval
- Interest in chemistry, biomedicine, or life sciences
- Curiosity, independence, and clear communication
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive
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Intern Data Science employer: Elsevier B.V.
Elsevier B.V. is an exceptional employer that fosters a collaborative and innovative work culture in the heart of Oxford. With a strong focus on employee growth, team members are encouraged to develop their skills through continuous learning opportunities while working on cutting-edge technology in an Agile environment. The company offers competitive benefits and a supportive atmosphere, making it an ideal place for those seeking meaningful and rewarding employment.
