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About the Role

Tabula is seeking a Research Scientist to contribute to the core computational and physics-based modeling efforts of an AI-first therapeutics company. This research-oriented role is ideal for a computational physicist or an individual with a similar quantitative, simulation-heavy background who excels in numerical methods, large-scale simulation, and modeling complex dynamical systems, and desires to tackle challenging technical problems with a direct link to real-world impact.

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.

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.
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.
Strong quantitative and computational judgment, ability to learn quickly, and excitement to work closely with scientists on a hard interdisciplinary problem.

Skills

Python
Modern scientific-computing stack
Modern machine learning stack (e.g., PyTorch)

Location

Remote

Work Type

Full-time

Experience Level

Early-stage role

Education Level

Ph.D. in Physics or a closely related quantitative field

About the Company

Tabula is building an AI-first therapeutics company focused on bacteriophages to design better therapies for hard-to-treat infections.
The company believes drug and therapy discovery will become increasingly computational.
Tabula's scientific work involves developing physics-based mathematical models of phage–bacteria interaction dynamics and large-scale numerical simulations.
An in-house wet lab generates experimental data to calibrate, test, and validate the physical models.
Tabula owns its data generation loop, allowing for continuous improvement of the system.
Phages offer a relatively short path from model output to real-world impact.
The company aims to use computational and physics-based modeling to design living therapies.
Tabula is an early-stage company with room to shape research direction and company strategy.