Information Scientist - Biomedical Data & AI

Are you curious about how AI is transforming biomedical research? A successful pharmaceutical company is looking for an Information Scientist to join a forward-thinking team working at the cutting edge of information science, AI and pharmaceutical R&D.

This role is ideal for someone who enjoys exploring new technologies, applying AI to real scientific challenges and helping researchers unlock insight from complex biomedical literature.

What you’ll be doing

* Using AI, NLP and LLMs to mine, summarise and analyse biomedical literature

* Designing smarter workflows for content analytics and knowledge management

* Supporting pharmaceutical R&D through high-quality, FAIR data and semantic technologies

* Acting as a subject matter expert for AI-driven content analytics

* Collaborating with cross-functional teams across science, data and digital

* Championing ethical, compliant and responsible use of AI

* Training and enabling teams to get the most from modern content analytics tools

What we’re looking for

* Background in Drug Discovery, Biomedical Research or similar with an ability to interpret scientific literature

* Experience or strong interest in NLP and LLM technologies (transformers, RAG, prompt engineering)

* Python and AI frameworks for text analytics

* Knowledge of ontologies, knowledge graphs and semantic technologies

* Confident communicator who enjoys working with diverse stakeholders

* Curious, adaptable and comfortable in a fast-evolving environment

Why apply?

* Work at the intersection of AI and biomedical science

* Influence how scientific knowledge is discovered and shared

* Join a collaborative, innovative and future-focused environment

The role is offered on an initial 12 month contract; the job holder is expected to work from the company's HQ in Slough minimum 2 days/week.

(NLP), Large Language Models (LLMs), Machine Learning, Text Analytics, Literature Mining, Retrieval Augmented Generation (RAG), Prompt Engineering, Python, Knowledge Graphs, Ontologies, Semantic Technologies, London, Slough, Reading, Oxford, VRS
9353SE