--- title: 'Research Scientist (Machine Learning), London at Isomorphic Labs' canonical: 'https://feeny.ai/job/research-scientist-machine-learning-london-isomorphic-labs-london-8serqn8jwx3z' type: 'job' last_seen: '2026-09-08' --- # Research Scientist (Machine Learning), London at Isomorphic Labs - **Company:** Isomorphic Labs - **Location:** London, United Kingdom - **Posted:** 2024-07-06 - **Last confirmed live:** 2026-09-08 - **Apply:** https://job-boards.greenhouse.io/isomorphiclabs/jobs/5224363004 ## Job description Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery. Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture. The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you. ## About Iso Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI. Research Scientist (Machine Learning), London ## Your impact As a Research Scientist in machine learning (ML), 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 conceive, design, and develop cutting edge machine learning algorithms to unlock new modelling and predictive power 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. Depending on your experience: You will create and lead projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems with deep learning - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs You will be instrumental in leading greenfield machine learning based research projects, building the models, and algorithms that will power our platform to transform the drug discovery world as we know it. ## What you will do - Contribute to our research directions in machine learning by using your extensive knowledge of the field to apply world-leading ML algorithms to drug discovery. - Identify and create novel ML techniques and the required data to train. - Develop the architectures and training algorithms of machine learning models. - Analyse and tune experimental results to inform future experimental directions. - Implement and scale training and inference engineering frameworks. - 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 machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation. - Strong knowledge of linear algebra, calculus and statistics. - Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas. - A passion for applying ML research to real world problems. - Depending on your experience: project supervision, leadership, or management. ## Nice to have - PhD in machine learning or computer science. - Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases. - 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 extraordinary company We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, 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. 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, and would 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). 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. Please note that when you submit an application, your data will be processed in line with our [privacy policy](https://www.isomorphiclabs.com/applicant-and-candidate-privacy-policy). >> [Click to view other open roles at Isomorphic Labs](https://www.isomorphiclabs.com/work-with-us#current-job-openings) ## About Isomorphic Labs ## Company Overview - **One-liner**: Isomorphic Labs is an AI-driven drug discovery company building on AlphaFold to accelerate the design of novel therapeutics and solve disease at digital speed. - **Entity Type**: Private (Series B) - **Headquarters**: London, United Kingdom (with an office in Lausanne, Switzerland) - **Founded**: 2021 - **Founders**: Sir Demis Hassabis, PhD (CEO) ## Core Business - Primary industry/industries: Biotechnology, AI-powered Drug Discovery, Healthcare - Target customers: B2B (pharmaceutical and biotech partners such as Johnson & Johnson) - Mission or purpose statement: "To one day solve all disease with the help of AI." ## Products & Services - **Isomorphic Labs Drug Design Engine**: A suite of predictive and generative AI models that go beyond AlphaFold to model complex biological phenomena, design novel molecules, anticipate drug performance, and accelerate scientific discovery at digital speed. - **Research Collaborations**: Strategic partnerships with major pharmaceutical companies (e.g., Johnson & Johnson) to co-develop drug candidates across multiple therapeutic areas. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed (recent Series B completed in February 2025) - **Key Metric**: Total Funding — Series B investment round announced February 2025 (amount not disclosed); prior funding from Alphabet as a subsidiary - **Notable Investors/Partners**: Alphabet (parent company, including Google DeepMind and Google Cloud); Johnson & Johnson (research collaboration) - **Growth Signals**: Expansion into Lausanne, Switzerland (new office); continued hiring across AI, science, and engineering roles; building on Nobel-winning AlphaFold technology; partnerships with top-tier pharma ## Competitive Advantages - **Frontier AI Access**: Sits within the Alphabet ecosystem alongside Google DeepMind, providing unique access to cutting-edge AI research and AGI development. - **AlphaFold Foundation**: Built directly on the Nobel Prize-winning AlphaFold system, giving the company a massive head start in computational biology. - **Interdisciplinary Team**: Combines world-class drug discovery experts with machine learning specialists in a high-velocity, high-trust culture. - **Ethical Framework**: Deeply integrates responsible AI development and ethical considerations into drug discovery. ## Strategic Focus - Current priorities: Scaling the Drug Design Engine, expanding partnerships with pharma, building out the Lausanne office, and advancing multiple drug discovery programs toward clinical candidates. - Long-term direction: Realizing the promise of "digital biology" to transform how medicines are discovered and developed, with the ultimate goal of solving all disease. ## Why Work Here - **Culture**: Described as "high-velocity, high-trust" — defined by urgency, curiosity, and collaboration. Core values: Brave, Determined, Together, Thoughtful. - **Remote/Hybrid**: Hybrid working model is supported; specific policies discussed during recruitment. - **Perks**: Generous employee benefits, development opportunities, access to frontier AGI research, and a mission-driven environment focused on world-changing impact. - **Engineering Culture**: Interdisciplinary teams working at the intersection of AI, biology, and medicine; emphasis on continuous learning and innovation. - **Team**: Led by a Nobel laureate (Demis Hassabis) and staffed by leaders from DeepMind, academia, and pharma. ## Sources 1. [isomorphiclabs.com](https://www.isomorphiclabs.com/) 2. [isomorphiclabs.com/careers](https://www.isomorphiclabs.com/careers) 3. [isomorphiclabs.com/life-at-iso](https://www.isomorphiclabs.com/life-at-iso) 4. [isomorphiclabs.com/work-with-us](https://www.isomorphiclabs.com/work-with-us) 5. 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