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 Computational Biologist with multi-disciplinary skills in computational biology, machine learning, and applied mathematics to join our team. This role bridges the gap between sequence-level design and systems-level dynamics, focusing on the development and application of sophisticated models that integrate diverse biological data.
The ideal candidate will be adept at building data-driven, mechanistic, and hybrid models to decipher complex biological processes and guide the engineering of therapeutic molecules and systems. You will leverage everything from high-dimensional omics datasets to time-course bioprocess data to create predictive models that drive genetic design and optimize bioprocess development. Join our team to contribute at the cutting-edge of innovation in biology and computational science, shaping the future of therapeutic innovation.
About The Role
- Design and implement sophisticated models—including data-driven (ML/AI), mechanistic (e.g., ODE-based), and hybrid approaches—to predict and optimize the performance of biologics and vector manufacturing processes.
- Develop models that predict functional outcomes such as transgene expressibility, protein stability, and product quality attributes from nucleic acid and amino acid sequence features
- Develop new models to predict developability attributes such as expressibility, secretability, aggregation, and stability of biologics, from sequence.
- Create multi-scale models of cellular behavior, integrating omics data (RNA-seq, proteomics, etc.) to simulate gene expression, protein secretion dynamics, metabolism, and cell phenotype.
About You
- You have a Ph.D. in Bioengineering, Computational Biology, Computer Science, Applied Mathematics, or a related quantitative field.
- You are proficient in sequence-based analysis and have hands-on experience integrating large-scale omics datasets (e.g., NGS, RNA-seq, proteomics) to inform model development and validation.
- You are an expert in applying machine learning and advanced mathematical techniques (e.g., dynamical systems, differential equations, stochastic modeling) to biological systems, with at least 3 years of experience in a pharmaceutical or biotechnology industry setting.
- You have a strong background in modeling dynamic biological systems, such as gene regulatory networks, metabolic pathways, or cell population dynamics.
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.
Compensation Range: $150K - $175K
