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Greater London, England, United Kingdom
Hybrid
Computational Protein Designer
We are seeking a Computational Protein Design Scientist to join our team working at the interface of generative AI and synthetic biology. Working closely with our Lead Computational Protein Designer, you will play a key role amongst a team of scientists designing and engineering proteins for specific functions. This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. Using your blend of computational expertise and in-depth biochemical understanding of proteins, you will generate insights to improve protein functionality and operate at the interface between our machine learning and experimental platform units, working closely to seamlessly integrate AI generations and lab validation data.
At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.
Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.
We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.
You are a computational protein designer. You have a proven track record of running protein design campaigns end-to-end, successfully leveraging novel computational tools and knowledge of biochemistry or structural biology to design proteins to functional requirements and applications in synthetic biology.
You are a generative modelling enthusiast You have AI generative modeling experience, including model training and large scale inference.
You are a successful scientist. You have a PhD (or equivalent industry experience) in computational biology, bioinformatics, computer science, biochemistry, structural biology, physics, biophysics, bio/chem engineering, or a related field. Your research experience was in protein biochemistry using computational expertise.
You collaborate with experimentalists. You have experience collaborating with experimental (i.e. wet lab) teams to achieve protein design objectives.
You are an owner. You have a proven track record of delivering successful commercial and / or academic research projects, demonstrated through publications, patents, and/or commercially impactful outcomes, as well as other contributions to the scientific community.
You are a connector. You love to connect people and enable them to perform at their highest levels. You have excellent communication and presentation skills with the ability to convey complex scientific concepts to both technical and non-technical audiences.
You are a mission driven innovator. You are passionate about making a positive impact on the world, whether it's for patients, partners or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies.
You thrive in a dynamic and ambiguous environment. You excel in a fast-paced setting where goals must be achieved efficiently and urgently. You have a keen eye for creating, then optimizing processes to improve speed and repeatability. You are an advocate for lab automation, both through hardware and software
You have experience with generative AI. You have experience leveraging generative AI (or other machine learning models) in synthetic biology applications.
You have experience with homology-based and structural bioinformatics, and are able to answer scientific questions using very large databases.
You have helped scale a young biotech before. You have worked in startups and helped the company grow.
Leverage our proprietary generative AI models to design proteins for experimental validation:
Analyze protein design problems based on functional requirements, biochemistry, structural biology and sequence homology
Generate designs using our proprietary generative AI models and optimize designs for experimental validation
Coordinate with our lab-based protein engineers to plan and optimize the design process and validation strategy
Leverage our proprietary data to improve our models:
Analyze and leverage our experimental results to improve the next round of designs and increase our success rate over validation rounds
Collaborate with machine learning scientists to fine-tune and prompt our models
Collaboration and communication:
Be an effective interface between machine learning model development and experimental validation
Capture bioengineering learnings and feedback to our machine learning unit, and vice versa
Foster a collaborative and innovative environment, proactively finding opportunities to innovate and create clarity and alignment between different units
Contribute to our computational tools:
Help improve the way we use, serve and integrate our AI models, by feeding back to the software engineers and foundational machine learning unit
Help improve our data management systems and workflows
Scientific excellence and self development:
Work to the highest scientific standards (publication-grade work)
Stay on top of relevant developments in synthetic biology
Continue building your understanding of generative AI as well as expanded areas of protein and cell biology
Participate in knowledge sharing, e.g. organize and present at our internal reading group.
Attend and present at conferences when relevant
We offer strongly competitive compensation and benefits packages, including:
Private health insurance
Pension/401(K) contributions
Generous leave policies (including gender neutral parental leave)
Hybrid working
Travel opportunities and more
We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
