Research Scientist, Quantum Chemistry and Machine Learning, London London

Research Scientist, Quantum Chemistry and Machine Learning, London

London

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'll 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 you will play an exciting role in building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world as we know it.

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading engineers and scientists to simulate biochemistry on a computer thus helping us develop cutting edge predictive models which will be critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

You will be instrumental in leading computational chemistry based research projects, predicting relevant experimental quantities and helping to generate data to train algorithms that will power our platform to transform the drug discovery world as we know it.

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

• 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.
• Depending on your experience: project supervision, leadership, or management.

Nice to have

• PhD in chemistry or physics.
• Relevant research experience to the position 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 biological or chemistry software
• Experience working with real-world datasets
• Experience with ML on accelerators
• Experience in any of: 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- Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day.

Brave- Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less.

Determined- Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we.

Together- Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere.

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.

We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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, andwould require you to be able to come into the office 3 days a week(currently Tuesday, Wednesday, and one other day depending on which team you’re in). As an equal opportunities employer, we are committed to building an equal and inclusive team. If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call.

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