About Basecamp Research and why this is an exciting opportunity:

Basecamp Research is building a generalisable platform for predicting the real world function, performance and behavior of proteins and to enable custom, product specific, one-shot design. To do this, we have purpose built an unprecedented protein AI resource - our knowledge graph of natural biodiversity that links never-seen-before proteins to their environmental, geological, and biological context from the most extreme and biodiverse places on earth. Our knowledge graph already beats the size of major public data resources in sheer number of proteins and excels when considering the coverage of sequence space (we are 4x less redundant than UniProt).

Having just closed our Series A financing, we have set ourselves the ambitious goal of being the leader in the AI-based design of proteins, and with our unparalleled ability to understand the context of protein evolution, we are looking for someone with a bold vision to lead this effort. The successful candidate will be the most senior contributor to our protein AI code-base and build & lead a team of fellow AI scientists/engineers. Beyond the access to unprecedented data, ethically sourced through access-benefit partnerships with nature parks around the world, the Protein AI Lead will coordinate exciting collaborations with leading academic groups and be in charge of landmark publications and entering competitions in this space. With our scalable, fast and globally operational discovery engine (from Antarctica to volcanic islands), the protein AI lead will also be the key decision maker on which environments and places on our planet to get contextualised protein sequence data from next.

We've raised $30M from True Ventures, Valo Ventures, Systemiq Capital, Hummingbird Ventures and Blue Horizon. There has never been a more exciting time to join us. 

About you

• An MSc or PhD in Computational Biology, Biophysics, Math, Statistics, ML, Computer Science or similar

• At least 3 years of experience managing an ML or AI team in the Life Science industry
• Track record of successful leadership
• Strong understanding of deep-learning methods for structural and functional characterisations of protein sequences, and design thereof
• Industry-relevant experience of deep learning applications in product development and commercial settings, ideally in the Life Sciences
• Strong knowledge of neural network architectures such as transformers, autoencoders, convolutional neural networks, large language models, attention models
• Excellent scripting experience in Bash & Python and experience with deep learning frameworks such as TensorFlow or PyTorch
• Experienced in cloud environments (AWS preferred)
• A relevant publication record
• Excellent communication skills and ability to work closely with interdisciplinary teams

Additional Skills (desired but not required)

• Experience with protein bioinformatics/engineering or molecular modeling software such as PyMOL, Rosetta, or Schrodinger
• Experience with / knowledge of graph algorithms and graph convolutional neural networks
• Knowledge of data pipelining (e.g. via Airflow) and prior experience of cloud-based ML model deployment
• Experience with Agile systems
• Experience with neo4j/cypher
• Previous experience in product or customer-facing roles in the biotech sector

What we can offer you in return

• Opportunity for leadership from day 1 and career development within our growing start-up
• An unprecedented and ethically sourced data resource for protein design
• Collaboration with leading academic groups / institutions and authorship on publications resulting from this position
• Ownership of fast-moving, ambitious projects with real-world impact.
• A fun, flexible and supportive work environment in the centre of London with an emphasis on team performance and personal development.
• Being a key, senior decision maker in the first company that builds the bridge between biodiversity and biotechnology
• A competitive salary & generous stock option plan.
• Exploring the world’s untapped biodiversity.
• Conferences, events, and training resources
• Resources to build a network of advisors and peers who are leaders in the field of protein AI/design
• Cycle-to-work scheme
• An international and diverse team