Research Scientist

About Tabula

Tabula is building an AI-first therapeutics company focused on bacteriophages to design therapies for hard-to-treat infections.

We are hiring a Research Scientist to help build the computational and physics-based modeling core of the company. This is a research-oriented role for a computational physicist (or someone with an equivalent quantitative, simulation-heavy background). We are looking for someone who is strong in numerical methods, large-scale simulation, and modeling of complex dynamical systems, who likes difficult technical problems, and wants to work on something where the connection between model quality and real-world impact is unusually direct.

You will develop physics-based models of phage–bacteria infection dynamics, design and run large-scale numerical simulations, and validate those models against experimental data in partnership with our wet lab. You will also help shape research direction, model quality, experimentation standards, and the relationship between computational and biological sides.

• 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 real therapies for real patients.

• 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 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; familiarity with the modern machine learning stack (e.g., PyTorch) is a plus.
• Good research judgment about which ideas are worth testing and how to evaluate them.
• 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.

We do not require prior biology experience; instead we need strong quantitative and computational judgment, quick learning, and enthusiasm for interdisciplinary work.