About this role
Data Science Internship
Cambridge
AstraZeneca is a global, science-led biopharmaceutical business and its innovative medicines are used by millions of patients worldwide. AstraZeneca Summer Internships introduce you to the world of ground-breaking drug development, embedding you in highly dedicated teams, committed to delivering life-changing medicines to patients. Our 10–12-week program is designed for undergraduate, master's, and doctoral students. We offer exciting opportunities across Research & Development, Operations, and Enabling Units (Corporate functions). Our internships immerse students in the pharmaceutical industry, allowing the opportunity to contribute to our diverse pipeline of medicines whether in the lab or outside of it.
You will feel trusted and empowered to take on new challenges, but with all the help and guidance you need to succeed. This internship will help you develop essential skills, expand your knowledge, and build a network that will set you up for future success. You will be surrounded by curious, passionate, and open-minded professionals eager to learn and follow the science, fostering your growth in a truly collaborative and global team.
Introduction to role
Join us at the Center for Artificial Intelligence (CAI) and Data Science & Modelling unit, where we are committed to accelerating biomedical research through the innovative application of machine learning. In this role you will work on topics around multi-task learning for developability property prediction for antibodies. In particular you will work on our in-silico developability property prediction framework that supports projects across oncology and biopharma for antibody design. The internship offers a unique chance to conduct high-impact research at the intersection of AI and drug discovery, focusing on projects that are pivotal to our research and development portfolio.
Accountabilities
As an intern, you will be engaged with several key responsibilities, including:
Develop a multi-task deep learning framework for antibody developability properties, including defining the ML modeling strategy and designing optimization approaches for a heterogeneous set of properties.
Implement MLOps best practices from the outset of the project.
Perform in silico predictions to assess antibody properties and validate results against experimental measurements.
Collaborate with experienced scientists to benchmark the multi-task learning framework against existing developability predictors.
Analyze heterogeneous datasets (public and internal) related to developability, and carefully clean and standardize them.
Essential Skills/Experience
The ideal candidate will possess the following skills and experience:
Essential:
PhD candidate in bioinformatics, computational biology, computer science, or a related field.
Knowledge of deep learning optimization techniques, especially multi-task learning.
Hands-on experience with machine learning frameworks and in silico modeling methods.
Strong programming skills in Python.
Excellent analytical and problem-solving abilities, with a demonstrated interest in antibody design and development.
Proven ability to collaborate in cross-functional teams and communicate scientific concepts effectively.
Desirable:
Experience with language models for biological sequences.
Previous experience working on developability data or therapeutic antibody design.
This internship is a valuable opportunity to immerse yourself in the forefront of therapeutic antibody discovery, with access to the necessary computational resources and mentorship from leading experts in the field. If you are ready to transform your technical knowledge into real-world applications, we encourage you to apply and become a part of our team driving innovation at AstraZeneca. Our collaborative environment is designed to help you grow professionally and personally, surrounded by passionate individuals eager to make a difference.
AstraZeneca is where you can immerse yourself in groundbreaking work with real patient impact.
Trusted to work on important projects, you’ll have the independence to take on new challenges while receiving all the guidance you need to succeed. Our collaborative environment is designed to help you grow professionally and personally, surrounded by passionate individuals eager to make a difference.
Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca, starting with the 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 reasonable adjustments/accommodations, please complete the section in the application form.
Ready to make an impact? Apply now and join us on this exciting journey!
#Earlytalent
Date Posted
23-Jan-2026Closing Date
06-Feb-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.Other facts
About AstraZeneca
We're transforming the future of healthcare by unlocking the power of what science can do for people, society and the planet. For more information, visit www.astrazeneca.com.
Community Guidelines: bit.ly/2MgAcio
What you'll do
- As an intern, you will develop a multi-task deep learning framework for antibody developability properties and implement MLOps best practices. You will also collaborate with experienced scientists and analyze heterogeneous datasets related to developability.
Ready to join AstraZeneca?
Take the next step in your career journey