Biometrics AI Science Placement: Oncology Data & ML

AstraZeneca; Macclesfield; On-site; GBP 25,000 - 31,000; Full time

Job summary

AstraZeneca in Macclesfield is offering a 12-month University Industrial Placement Student (UIPS) in Biometrics – AI Science Specialist. Based in the UK, the role provides a £28,000 base salary, plus bonus and flexible benefits, and a hands-on pathway into AI-driven drug development.

You will join Oncology Biometrics Information Practice and work with Python/R, developing AI-enabled tools to enhance evidence discovery and literature search workflows, while learning from experienced colleagues.

Qualifications

• Undergraduate/integrated Master’s degree in CS, data science, engineering, maths, statistics, AI, or related field.
• Hands-on coding experience in Python, R, or Julia.
• Interest in applying AI/data science to real scientific/business challenges.
• Good organization, collaboration and communication skills.

Responsibilities

• Gain hands-on experience in drug development AI/data science within Oncology Biometrics.
• Apply coding, analytical, and problem-solving skills to real business challenges.
• Develop experience using Python/R for data analysis, automation, and experimentation.
• Apply AI/machine learning techniques to scientific or operational problems.
• Contribute to AI-enabled tools to enhance literature search and evidence discovery.

Skills

Python

R

Julia

AI/ML basics

Team collaboration

Strong communication

Problem-solving

Curiosity to learn

Education

Undergraduate or integrated Master’s in CS/Data Science/Engineering/Math/Statistics/AI

Tools

scikit-learn

TensorFlow

PyTorch

spaCy

Git

Power BI

Job description

AstraZeneca in Macclesfield is offering a 12-month University Industrial Placement Student (UIPS) in Biometrics – AI Science Specialist. Based in the UK, the role provides a £28,000 base salary, plus bonus and flexible benefits, and a hands-on pathway into AI-driven drug development.

You will join Oncology Biometrics Information Practice and work with Python/R, developing AI-enabled tools to enhance evidence discovery and literature search workflows, while learning from experienced colleagues.