Research Scientist (Quantum Chemistry and Machine Learning), London

Isomorphic Labs is a new Alphabet company that is reimagining drug discovery through a computational- and AI-first approach. We are on a mission to accelerate the speed, increase the efficacy and lower the cost of drug discovery. You will be working at the cutting edge of the new era of 'digital biology' to deliver a transformative social impact for the benefit of millions of people. Come and be part of a multi-disciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring, collaborative and entrepreneurial culture.

Your impact as a Research Scientist in Quantum Chemistry and Machine Learning includes:

• Building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world.
• Partnering with leading engineers and scientists to simulate biochemistry on a computer, helping to develop cutting edge predictive models critical to the organisation's success.
• Leading computational chemistry based research projects, predicting relevant experimental quantities and generating data to train algorithms.

What you will do:

• Contribute to our drug development projects by using your extensive knowledge of theoretical chemistry to run accurate and relevant simulations.
• Develop the computational infrastructure to run simulations at scale through our cloud compute platform.
• Generate synthetic datasets that help improve the performance of our ML models.
• Report and present research findings and developments clearly and efficiently to both other ML scientists and scientists of different disciplines.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.

Depending on your experience:

• Provide technical mentorship and guidance to the ML research community, advising on projects and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems.
• Cultivate a diverse and inclusive research culture.

Skills and qualifications:

• Essential: PhD or equivalent practical experience in a technical field; a proven track record in applying computational chemistry to predict relevant experimental quantities in an applied research field; strong scientific knowledge of biology, chemistry, or physics; exposure to applied ML research.
• Nice to have: PhD in chemistry or physics; relevant research experience such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases; experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas; strong knowledge of linear algebra, calculus and statistics; experience working in a scientific environment across disciplines (particularly biology, chemistry, physics); experience working with biological or chemical data and software; experience with ML on accelerators; experience in large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL.

Culture and values:

We are guided by our shared values. It’s not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it.

• Thoughtful: Curiosity, creativity and care.
• Brave: Fearlessness, initiative and integrity.
• Determined: Confidence in our hypothesis, urgency and agility needed to deliver on it.
• Together: Connection, collaboration across fields and catalytic relationships.

Creating an inclusive company:

We believe that to be successful we need our teams to reflect and represent the populations we are striving to serve. We’re working to build a supportive and inclusive environment where collaboration is encouraged, learning is shared and every employee feels like they truly belong. We value diversity of experience, knowledge, backgrounds and perspectives, and harness these qualities to create extraordinary impact.

Hybrid working:

It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, requiring you to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in).