Research Scientist

Tabula Bio•San Francisco, CA

About The Position

Tabula is building an AI-first therapeutics company focused on bacteriophages to design therapies for hard-to-treat infections, addressing the growing problem of antibiotic resistance. The company's approach integrates physics-based mathematical modeling and large-scale numerical simulation of phage-bacteria interactions with an in-house wet lab for data generation, calibration, testing, and validation. This unique model generation loop allows for continuous improvement and a shorter path from research to real-world impact. The role is for a computational physicist or equivalent with expertise in numerical methods, large-scale simulation, and complex dynamical systems, who is motivated by challenging technical problems with direct real-world impact.

Requirements

A Ph.D. in Physics or a closely related quantitative field (applied mathematics, computational science, or similar), or equivalent research experience.
Strong background in numerical methods, large-scale simulation, and the modeling of complex dynamical systems, including systems governed by partial differential equations.
Depth in one or more of: statistical mechanics, optimization theory, probabilistic and statistical methods, and numerical stability and error analysis.
Experience with large-scale scientific computing and high-performance computing environments.
Fluency in Python and the modern scientific-computing stack.
Comfort working in an early-stage environment where the problems are hard and the path is still being defined.
Ability to work closely with domain experts outside your own field.

Nice To Haves

Familiarity with the modern machine learning stack (e.g., PyTorch) is a plus.
Substantial modeling and simulation work, not just building products on top of model APIs.
Enjoy designing experiments and learning from ambiguous results.
Excited by the idea of applying physics and computation to something more concrete than the usual software treadmill.
Want work to be tied to outcomes in the real world.
Interested in helping build a company where computational and physics-based research is central, not decorative.

Responsibilities

Develop physics-based theoretical and computational models of phage–bacteria infection dynamics, applying numerical simulation, statistical mechanics, and optimization theory.
Investigate the underlying biophysics of phage infection — binding kinetics, replication dynamics, and population-level interactions — and translate these physical phenomena into tractable mathematical and computational form.
Design and implement numerical methods and software for large-scale simulation and analysis of these physical systems.
Perform mathematical analysis of the underlying models, including numerical stability analysis, error analysis, and validation against experimental data.
Analyze experimental data using mathematical and statistical methods to infer physical parameters and constrain the underlying models.
Design and conduct computational experiments, in close coordination with our wet-lab scientists, to test and refine the models.
Help define the research roadmap for how Tabula's models should improve over time, and build better practices around experimentation, evaluation, and reproducibility.
Help a small team build an AI-first company whose output is not content or software alone, but real therapies for real patients.