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

Job description

**12 Month University Industrial Placement Student (UIPS):** **Biometrics – AI Science Specialist** Macclesfield, UK £28,000 Base Salary, Bonus and Flexible Benefits **About AstraZeneca:** AstraZeneca is a global, science-led, patient-centred biopharmaceutical company focused on discovering, developing, and delivering medicines for some of the world’s most serious diseases. At AstraZeneca, you will be part of work that matters—work that helps bring life-changing medicines to patients. At AstraZeneca, you will be empowered to push the boundaries of science, develop your skills, and contribute to work that makes a difference to patients, society, and the future of medicine. For students looking for a placement with real purpose, this is an opportunity to apply technical skills to meaningful challenges, learn from experts working at the intersection of science and technology, and gain experience in a company where innovation is central to improving patient outcomes. **About the University Industrial Placement Student (UIPS) Programme:** **Join a truly inclusive and supportive international team.** As an AstraZeneca placement student, you will be part of a wide support network from day one. You will have a dedicated supervisor, access to a supportive early talent community, and opportunities to connect through Employee Resource Groups and the wider student cohort. We want our placement students to do more than observe. You will be encouraged to ask questions, share ideas, and contribute to work that has genuine value. Throughout your placement, you will build technical knowledge, professional confidence, and an understanding of how your work connects to the bigger picture in pharmaceutical R&D. Whether you are looking to deepen your coding and analytical skills, explore the practical use of AI in healthcare, or gain experience in a collaborative and fast-moving environment, AstraZeneca offers a placement where you can learn, grow, and make an impact. Are you ready to take the next step in your career? Apply today. **We discourage multiple applications to our UIPS opportunities. Please therefore submit one application to the opportunity that best matches your skills and aspirations. We reserve the right to review and progress one application per candidate based on the role's criteria and candidates' skills.** **Macclesfield** The Macclesfield Campus is an essential part of AstraZeneca’s UK operations and the second-largest operational site in the company’s global network. Spanning approximately 100 acres and home to around 4,500 people, the site brings together Operations, R&D, G&A, IT, OBM and other functions in one location. For placement students, this creates a uniquely rich learning environment. You will be part of a vibrant campus community with opportunities to collaborate, build your network, and gain exposure to a wide range of teams and career paths. **About the Opportunity:** Oncology Biometrics (OBM) is the home of early- and late-stage drug development biometrics activity at AstraZeneca. We support all aspects of clinical development, including strategy, clinical trial design, data collection, analysis, reporting, and interpretation to inform high-quality decision-making across AstraZeneca’s drug projects. This placement sits within the **Oncology Biometrics Information Practice team** and is ideal for students interested in **AI science**, **applied data science**, and the **use of technology** to improve how scientific knowledge is identified, analysed, and used in drug development. As part of the team, you will explore how **AI, machine learning, natural language processing, and automation** can support oncology projects and improve internal workflows. A key part of the placement will involve contributing to **AI-enabled tools** and approaches that **enhance and optimise the scientific literature search process**. This will help teams find, review, and use relevant evidence more efficiently to support scientific and drug development decision-making. You will work on real business and scientific challenges, applying coding and analytical 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. **Qualification, Skills & Experience** **Required:** - **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.** - **Experience working on projects involving machine learning, data analysis, AI, automation, or related technical problem-solving.** - **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.** **Desirable:** - **Awareness of natural language processing concepts and tools.** - **Experience using AI libraries or frameworks** such as scikit-learn, TensorFlow, PyTorch, spaCy, or similar. - **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.** - **Experience with data visualisation tools**such as Power BI, Tableau, matplotlib, or similar. - **Experience using version control systems**such as Git. - **Experience presenting technical findings to technical or non-technical audiences.** - **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 **This position is a 12-month fixed term contract.** **#EarlyTalent** AstraZeneca is proud to be ranked as a Top 100 ‘Best Student Employer’ in the UK by RateMyPlacement. Browse our reviews here ([link](https://www.ratemyplacement.co.uk/placement-review/159551/astrazeneca/industrial-placement-student-at-astrazeneca)) AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome applications from all qualified candidates, regardless of background or personal characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements. **Date Posted** 08-Sept-2026 **Closing Date** 02-Oct-2026Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.