Teams at The Biological Computing Company

Lead research on video-generation models for control and long-horizon rollouts. Design and scale architectures, own research workstreams from hypothesis to evaluation, identify risks, and translate biological compute insights into actionable models and platform capabilities while mentoring colleagues and collaborating with cross-functional teams.

Lead technical direction for a generative video modeling platform, design and scale video generation and control-oriented prediction models, improve long-horizon rollout fidelity, integrate physical priors and object-centric representations, anticipate architectural bottlenecks, and mentor the team to translate research into deployable systems.

Design and run experiments encoding information into living neural cultures; analyze large-scale electrophysiology/MEA recordings and neural population dynamics; derive computational principles and translate them into algorithms and ML models; build closed-loop research infrastructure and reusable analysis pipelines; own research workstreams and communicate findings across biology, AI, and engineering teams.