Multi-objective lead optimization for antibody discovery Internship

About AstraZeneca

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 multi-objective antibody design. You will dive into advanced approaches including protein language models, multi-objective Bayesian optimization and reinforcement learning, to improve current workflows for antibody design. 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:

• Extending a single-objective optimization framework to incorporate multiple objectives such as stability and solubility in antibody lead optimization.

• Conducting in silico predictions to assess antibody properties and validate these predictions using experimental KD measurements.

• Collaborating with experienced scientists to benchmark multi-objective optimization strategies against existing models.

• Exploring advanced reinforcement learning techniques such as Direct Preference Optimization (DPO) for enhancing optimization workflows.

• Analyzing publicly available affinity maturation datasets to validate the proposed methodologies.

• Contributing to the continuous improvement of our optimization framework 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.

• Familiarity with optimization techniques, particularly Bayesian optimization.

• Experience with machine learning frameworks and in silico modeling methods.

• Excellent programming skills in Python.

• 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.

Desirable:

• Experience with language models for biological sequences.

• Experience with reinforcement learning and generative models.

• 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.

Additional Information: Applications will be open until 28/02/2025. Start date is 16/06/2025 -05/09/2025 and you can expect to hear from us by the end of March 2025.

Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca, 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.

Ready to make an impact? Apply now and join us on this exciting journey!

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 and consider applications to join our team from all qualified candidates, regardless of their 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.