Our mission at Asimov is to advance humanity’s ability to design living systems, enabling biotechnologies with outsized benefit to society. We’re developing a mammalian synthetic biology platform––from cells to software––to enable the design and manufacture of next-generation therapeutics.
We are searching for a Senior or Principal Computational Biologist with an extensive track record of developing innovative approaches that utilize mechanistic models, machine learning, omics, deep learning, and AI (e.g. LLMs). At Asimov, predictive modeling and simulation are core to our platform. We genetically engineer living cells and refine our designs using an ever-expanding suite of computational design methodologies and sophisticated analysis of multiomics data. The ideal candidate is motivated by designing complex cellular systems, distilling insight from large biological datasets, and producing novel tools to be used by others. This is a unique opportunity to work at a nimble, forward-thinking synthetic biology startup and help build the foundation for engineering biology.
About the Role:
- Contribute to and lead initiatives to design and analyze engineered mammalian cell lines by developing robust and innovative computational approaches that utilize mechanistic models, multiomics, machine learning, deep learning, and AI.
- Work closely with bench scientists to develop experimental plans and analyze quantitative measurements with statistical rigor to gain biological insights and to train and validate models.
- Regularly dive deep into the multiomics stack to innovate on analysis techniques, algorithms, models.
- Present findings to our team, leadership, and partners.
- Pair with our software engineers to transition impactful computational approaches into our commercial software offerings.
- Contribute to Asimov’s long-term computational biology strategy.
About You:
- You are a highly skilled researcher and innovator with at least 5 years of experience in industry or academic research and with a published track record of developing new, impactful approaches to computational biology. A strong foundation in statistics and experimental design is a plus.
- You are passionate about joining a startup where teamwork, passion to learn, and excitement to engineer biology take precedence over process and ego.
- You have broad, proven expertise in solving difficult biology problems utilizing both classical and new computational biology approaches, including working with large multiomics datasets, machine learning techniques, deep learning methods, and AI/LLM-based approaches. Demonstrated interest in engineering biology is a plus.
- You have extensive knowledge of molecular biology and cellular biology, particularly in mammalian systems and/or cellular production systems.
- You have deep knowledge of public biological databases and their application for mammalian cell biology.
- You are expert in Python, R, and common bioinformatic toolkits, as well as with computational notebooks (Jupyter), version control (Git), and coding best-practices. You also have experience with cloud computing environments (GCP) and databases (SQL).
- You have a record of working closely with wet lab scientists to design experiments and interpret data to most effectively extract statistically and biologically meaningful insights.
- Experience with developing data applications (Streamlit, PyWebIO, Flask, Dash) is a plus.
We’re fueled by a vision to transform biological engineering into a fully-fledged engineering discipline. Should you join our team, you will grow with a constantly evolving organization and push the frontiers of synthetic biology. Company culture is key to Asimov, and ours is a culture of recombination; we believe that our mission can only be achieved by bringing together a diverse team with a mixture of backgrounds and perspectives.
