Thesis Work, 30 Credits – AI & Machine Learning for Drug Discovery

Are you passionate about AI, machine learning, and their applications in drug discovery? Join the MolecularAI group at AstraZeneca and contribute to cutting-edge research that is shaping the future of medicine.

About AstraZeneca:

AstraZeneca is a global, science-led, patient-centred biopharmaceutical company focusing on discovering, developing, and commercialising prescription medicines for some of the world’s most serious diseases. But we’re more than a global leading pharmaceutical company. At AstraZeneca, we're dedicated to being a Great Place to Work and empowering employees to push the boundaries of science and fuel their entrepreneurial spirit.

About the Opportunity:

As a Thesis Worker at AstraZeneca, you’ll find an environment that’s full of unique opportunities and exciting challenges. Here, you’ll have the opportunity to pursue your areas of interest whilst equally developing a broad skillset and knowledge base to get the best out of your experience. You’ll be working on meaningful projects to make an impact and deliver real value for our patients and our business.

Project Overview:

At AstraZeneca, our MolecularAI team is pioneering the use of advanced AI, machine learning algorithms, molecular simulation, and data science to develop models and tools that drive drug discovery. We have created several open-source platforms, including:

• ReInvent: A tool for molecular design using reinforcement learning.
• AiZynthFinder: A platform for synthesis planning.
• Maize: A manager for advanced simulation pipeline.

All our code is available at https://github.com/MolecularAI/

We are now seeking motivated master’s students to join our team and push the boundaries of these models, addressing their current limitations.

Potential Research Areas:

• Exploring Novel Deep Learning Architectures: Innovate with new AI frameworks for molecular design and synthesis.
• Developing Scaling Relations for Chemical Generative Models: Help understand how data size and quality control the efficiency and power of generative algorithms.
• Flow Matching and Diffusion Models for Atomic Point Clouds: Advance the modeling of atomic structures using cutting-edge techniques.
• Uncertainty and Multi-Objective Optimization: Improve model reliability and balance multiple objectives in drug design.
• Investigating Algorithms for Chemical Reaction Mapping: Create more accurate methods for predicting roles in chemical reactions.
• Combining Machine Learning and Physical Descriptors: Integrate AI with quantum mechanical calculations for more robust predictions.
• Binding Affinity Prediction with Machine-Learned Potentials: Develop efficient models for predicting how strongly drugs bind to their targets.

Essential Requirements:

• Ongoing studies on Master level.

Desirable Requirements:

• Knowledge in python programming, AI, machine learning, or algorithms.
• Studies in computer science, machine learning, AI, complex adaptive systems, or similar.
• A background in chemistry is beneficial but not required.

Why AstraZeneca:

AstraZeneca is a global, innovation-driven biopharmaceutical company that focuses on the discovery, development, and commercialization of prescription medicines for some of the world's most serious diseases. In addition to being one of the world's leading pharmaceutical companies, AstraZeneca is proud to provide a unique workplace culture that inspires innovation and cross-boundary collaboration. Within this environment employees are empowered to express diverse perspectives, and are made to feel valued, energized and rewarded for their ideas and creativity.

Next Steps:

We welcome your application as soon as possible, but ahead of the scheduled closing date 31st of October 2024. In the event that we identify suitable candidates ahead of the scheduled closing date, we reserve the right to withdraw the vacancy earlier than published.

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 follow all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.

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.