12 Month University Industrial Placement Student: Biometrics - AI Science Specialist

About the Company

Responsibilities

• ● alytical skills in a pharmaceutical R&D environment while learning from experienced colleagues. This means you will gain exposure not only to technical development, but also to how scientific literature searching and evidence gathering are used in practice across the drug development process.
• ● As a member of Oncology Biometrics' Information Practice team, you can expect to:
• ● Gain hands-on experience of the drug development process and how AI and data science can support oncology project teams.
• ● Apply coding, analytical, and problem-solving skills to real business challenges.
• ● Develop experience using Python, R, or similar tools to support data analysis, automation, and experimentation.
• ● Apply AI and machine learning techniques , including natural language processing, to scientific or operational problems.
• ● Explore innovative technologies that enhance knowledge discovery, workflow efficiency, and decision support.
• ● Contribute to internal team activities and functional forums and learn how data, technology, and science come together in drug development.
• ● Build understanding of how literature-based evidence supports scientific and project decision-making in the pharmaceutical setting.
• ● Work collaboratively with colleagues across Biometrics and drug development and gain exposure to cross-functional ways of working.
• ● Present your work within AstraZeneca, helping you build confidence in communicating technical concepts and findings to different audiences.
• ● This placement will give you valuable experience for future careers in AI, data science, machine learning, analytics, digital health, and technology-enabled pharmaceutical R&D.

Requirements

• ● Currently undertaking an undergraduate or integrated master's degree with the opportunity to spend 1 year in industry starting in September 2027 .
• ● Degree subject must be within computer science, data science, engineering, mathematics, statistics, artificial intelligence, or a related discipline.
• ● Hands-on experience coding in Python, R, or Julia through coursework, academic projects, or personal projects.
• ● Understanding of the basics of artificial intelligence and machine learning.
• ● Interest in applying AI and data science to real scientific or business challenges.
• ● Good organisational skills with the ability to plan, manage, and deliver small projects or assignments.
• ● Good collaboration and teamworking skills.
• ● Good written and verbal communication skills , with the ability to explain technical work clearly.
• ● Curiosity, willingness to learn, and enthusiasm for solving problems.
• ● To support your application, please include a cover letter highlighting any scholarships, publications, work experience or extracurricular activities demonstrating leadership and teamwork. Your cover letter should be included in the same document as your CV, and the uploaded file should be named in the format Surname, First name.
• ● Awareness of natural language processing concepts and tools.
• ● Some knowledge of the drug development process and how scientific evidence is used to support decision-making.
• ● Awareness of the scientific literature search process and how literature searching contributes to evidence gathering in a research or drug development environment.
• ● Interest in applying AI to improve literature searching, evidence discovery, and knowledge workflows.
• ● Interest in intelligent automation or AI-enabled decision-support tools.
• ● Interest in healthcare, life sciences, oncology, or pharmaceutical R&D.
• ● Applications Open: 4th September 2026
• ● Applications Close: 2nd October 2026
• ● Assessment Days: 28 & 29th October 2026
• ● Start Date: 6th September 2027