This is the role we keep open permanently. The work here is interesting enough that pure mathematics and frontier deep learning sit in the same team, applied to the same problem: measuring what biology is actually doing. It does not divide cleanly into research, infrastructure and product. The person who derives the estimator is usually the person who ships it, and the person who ships it is usually the first to discover where it breaks. Member of Technical Staff is our name for people who move across those boundaries, and for whom the problem matters more than the title.
What you would do
There is no fixed answer. Depending on who you are, it might mean training world models of human physiology on national-scale compute, making a statistical method rigorous enough to publish and robust enough to run in a hospital, building the data machinery that gets longitudinal clinical records to a GPU without losing what makes them clinical, or proving something about noise that changes what the platform can claim. What stays constant is the object of study: physiological and clinical time series, the mathematics of measurement, and the instruments we build to resolve biological change that coarser methods average away.
What we're looking for
- Evidence of exceptional ability in a quantitative discipline: mathematics, physics, computer science, quantitative finance, computational neuroscience, or a field we have not thought to list. We care about the evidence, not the credential. A proof, a system, a paper, a trading model, a repository.
- The instinct to build. Research that ends as an idea is half-finished here. We want people who consider a result unproven until it runs.
- Taste for the layer beneath the models. Measurement, inference, estimation, the structure of time.
How this works
We hire on a rolling basis. There are no application windows and no cycles: we read every application, and when the person is right, we make the role. Tell us what you have built or proven, and why the measurement problem is the one you want to work on.