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Research Internship on multi-fidelity learning from affinity data

icon building Company : Astrazeneca
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Job Description - Research Internship on multi-fidelity learning from affinity data

Research Internship on multi-fidelity learning from affinity data

Cambridge

AstraZeneca is a global, science-led biopharmaceutical business and its innovative medicines are used by millions of patients worldwide. AstraZeneca has long been an advocate of student work placement training. These placements 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. At AstraZeneca, you will engage in meaningful work within a pioneering research and development organization. This placement 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), where we are committed to accelerating biomedical research through the innovative application of machine learning. In this role you will collaborate on a project leveraging deep learning for antibody design. You will explore multi-fidelity models to leverage data from various sources for predicting antibody-antigen binding. You will work alongside leading experts in machine learning and antibody design, gaining hands-on experience in a supportive and dynamic setting. 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:
  • Building a multi-fidelity model for experimental antibody affinity data.
  • Extending the model to accommodate in silico data and evaluate the gains on prediction.
  • Adhering to software engineering best practices to deliver reusable code.
  • Analyzing publicly available affinity maturation datasets to validate the proposed methodologies.
  • Collaborating with experienced scientists on antibody lead optimization projects with potential applications in real-world therapeutic antibody design.

Essential Skills/Experience
The ideal candidate will possess the following skills and experience:

Essential:
  • Currently pursuing a PhD degree in bioinformatics, computational biology, computer science, or a related field.
  • Experience with machine learning and deep learning techniques.
  • Excellent programming skills (python) and familiarity with deep learning frameworks (e.g. pytorch)
  • Strong analytical and problem-solving abilities, with a keen interest in antibody design and development.
  • Ability to work collaboratively in a team environment and communicate scientific ideas effectively.
  • Must be at least 18 years of age at time of application.
  • Must have UK right-to-work status.
  • Must return to schooling at program close (candidates graduating before/during the programmes are ineligible)

Desirable:
  • Experience with multi-fidelity or multi-task modeling.
  • Familiarity with protein language models, structure prediction, and other in silico tools for antibody lead optimization
  • Previous experience working on affinity maturation 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

30-Jan-2026

Closing Date

13-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.
Original job Research Internship on multi-fidelity learning from affinity data posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.
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