Research Scientist (Machine Learning), Lausanne

ppIsomorphic 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, enabled by the incredible power of machine learning, and 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 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, and it starts with the culture at this company and with you. /p h3About Iso /h3 pIsomorphic 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 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 work across multiple therapeutic areas and drug modalities. We continually innovate on model architecture and develop 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. /p h3Research Scientist (Machine Learning), Lausanne /h3 h3Your impact /h3 pAs 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 partner with leading engineers and scientists to conceive, design, and develop cutting‑edge machine learning algorithms that unlock new modelling and predictive power critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, applying novel techniques and ideas to newly encountered computational biology and chemistry problems. /p h3What You Will Do /h3 ul liContribute to our research directions in machine learning by applying world‑leading ML algorithms to drug discovery. /li liIdentify and create novel ML techniques and the required data to train. /li liDevelop the architectures and training algorithms of machine learning models. /li liAnalyse and tune experimental results to inform future experimental directions. /li liImplement and scale training and inference engineering frameworks. /li liReport and present research findings and developments clearly to both ML scientists and scientists of different disciplines. /li liIterate collaboratively with scientists and domain experts, sharing your own domain experience. /li liSuggest and engage in team collaborations to meet ambitious research goals. /li /ul h3Depending on your experience /h3 ul liProvide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise. /li liProvide developmental support to other ML research scientists. /li liCreate, lead, and run ML research projects, fostering collaborative and diverse teams to solve high‑priority modelling problems. /li liCultivate a diverse and inclusive research culture. /li /ul h3Essential Skills and Qualifications /h3 ul liPhD or equivalent practical experience in a technical field. /li liA proven track record in machine learning using deep learning techniques, including designing new architectures, hands‑on experimentation, analysis, and visualisation. /li liStrong knowledge of linear algebra, calculus, and statistics. /li liExperience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas. /li liA passion for applying ML research to real‑world problems. /li liDepending on your experience: project supervision, leadership, or management. /li /ul h3Nice to have /h3 ul liPhD in machine learning or computer science. /li liRelevant research experience such as post‑doctoral roles, a proven track record of publications, or contributions to machine learning codebases. /li liExperience working in a scientific environment across disciplines (particularly biology, chemistry, physics). /li liExperience working with biological or chemical data and biological or chemistry software. /li liExperience working with real‑world datasets. /li liExperience with ML on accelerators. /li liExperience 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. /li /ul h3Culture and values /h3 pWe are guided by shared values. They help to guide our work and will continue to strengthen it. /p h3Thoughtful /h3 pThoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future‑making science every single day. /p h3Brave /h3 pBrave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less. /p h3Determined /h3 pDetermined 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. /p h3Together /h3 pTogether 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. /p h3Creating An Extraordinary Company /h3 pWe 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. /p pWe 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. /p h3Hybrid working /h3 pIt’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 be able to come into the office three 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. /p /p #J-18808-Ljbffr