AI Research Scientist - Immunoinformatics

About Us

Exscientia is an AI-driven pharmatech company committed to discovering, designing and developing the best possible drugs in the fastest and most effective manner. Exscientia developed the first-ever functional precision oncology platform to successfully guide treatment selection and improve patient outcomes in a prospective interventional clinical study, as well as to progress AI-designed small molecules into the clinical setting.

Our pipeline demonstrates our ability to rapidly translate scientific concepts into precision-designed therapeutic candidates, with more than 25 projects underway. By designing better drugs, faster, we believe the best ideas of science can rapidly become the best medicines for patients.

Role

As the Research Scientist (Immunoinformatics) you will be using your expertise to directly contribute to our mission: making better drugs, faster - by further improving the predictive and generative modeling capabilities of our AI technology platform. We are applying state-of-the-art AI methods to address a diverse range of important problems in biologics discovery and are constantly innovating if required tools are not sufficient or do not exist.

Some key challenges we are working on with our method development: How do we rapidly an accurately generate antibody structures bound to their target? How do we find the best one that can be advanced to clinical development by making and testing as few antibodies as possible? To address these and other problems we use methods such as graph neural networks to generate structures and docked complexes, deep architectures to predict properties and Bayesian optimization to decide what to make next.

You will have the opportunity to work in exciting areas of AI-driven biologics design like these as part of a talented and friendly team of research engineers with diverse scientific backgrounds.

This role is a great fit for researchers that are passionate about AI and equally keen on implementing methods that can and will be used to improve the drug discovery process.

You will have the opportunity to:

• Increase the accuracy and applicability of our predictive models through algorithmic or architectural improvements.
• Extend and improve our generative design capabilities through better models and algorithms.
• Enhance the explainability of our machine learning predictions through methods such as feature attribution and robust estimation of uncertainty.
• Develop cutting edge AI methods that can assist expert decision making - or even better, automate it
• Collaborate with research scientists and immunoinformaticians and use their feedback to improve our methods or create entirely new ones.
• Stay informed on the latest research in relevant scientific fields and analyze its potential impact on our capabilities.
• Interact with the larger AI communities by attending conferences or workshops and writing high-impact publications.

Requirements

• Master's or PhD degree or in artificial intelligence, machine learning, mathematics, physics, computer science or a related field with a comparable focus on analytical skills. Or an undergraduate degree in any one of these fields combined with comparable research experience from a professional career.
• Good understanding of statistics and how statistical concepts such as Bayesian inference are applied in machine learning.
• Ability to conduct novel research in a field of artificial intelligence such as machine learning or automated reasoning.
• Advanced Proficiency in Python or experience in one or more programming languages (e.g. Java, C/C++)
• Excellent interpersonal, oral, and written communication skills
• Strong team player with an inclusive mindset that is willing to listen and learn from others.
• Desire to bring novel AI research as quickly as possible into a production environment to ultimately deliver therapeutics to patients faster

Beneficial Skills & Experience

• Experience of developing and applying machine learning/deep learning algorithms to biological data
• Working experience in relevant state-of-the-art deep learning methods, such as graph neural networks, transformers, Gaussian processes, generative modelling and reinforcement learning.
• Presenting/publishing at AI-conferences
• Experience with cloud compute platforms such as AWS, GCP or Azure.
• Familiarity with major machine learning frameworks such as scikit-learn, TensorFlow or PyTorch for building machine learning models and deep neural network architectures.
• Hands-on experience with best software development practices and particularly in a collaborative environment.
• Experience with ML Ops, continuous integration and deployment (CI/CD) frameworks.
• Open source contributions or publications in academic journals demonstrating experience in developing machine learning techniques to solve scientific problems.
• Experience with high performance computing and/or cloud computing
• Understanding of the biologics research and development process

Benefits

• Work together to make a positive contribution to patients by revolutionising the pharmaceutical industry through AI-driven discovery.
• We will work with you to kick-start or further grow your career – from funding for professional development and conference attendance. To the opportunity to acquire valuable skills, work on problems that matter, and learn from world-class technological and scientific leaders.
• Opportunity to join an inclusive, collaborative and intellectually stimulating culture
• We will work with you to provide a highly competitive compensation as we continue to grow and thrive.
• Our team’s health and well-being is important to us we offer a generous holiday allowance, provide flexible working and remote working to encourage all of our team to manage their own work, time and life along with wellbeing and mindfulness support.
• When you are in the office, you will have access to a kitchen stocked with an endless supply of food for all employees. Along with access plenty of break out areas so you can get to know the people you are working with. Some of the best ideas start with a coffee break!
• Hear from our team why they enjoy working here