Back to job search
TimeTrace Labs logo

Member of Technical Staff

  • London, ON
  • On-site
  • Posted Oct 9, 2026
  • 1 position

Opens LinkedIn

Sign in to save this job
Employment type
Full-time
Experience level
Mid-level · 2+ years
Posting language
English
Working hours
40 hours per week
Seniority
Entry level

Job summary

Develop and apply mathematical and computational methods to measure biological change in physiological and clinical time series, including training models and building data infrastructure. Turn research into robust, deployable systems and investigate the limits of measurement and inference.

Job details

All open roles Technical Staff Member of Technical Staff Full-time London Technical Staff Open on a rolling basis 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. Apply for this role

What you’ll do

Develop and apply mathematical and computational methods to measure biological change in physiological and clinical time series, including training models and building data infrastructure. Turn research into robust, deployable systems and investigate the limits of measurement and inference.

Requirements

Demonstrate exceptional ability in a quantitative discipline, evidenced by work such as a proof, system, paper, trading model, or repository; no specific credential is required. Show an instinct for building and an interest in measurement, inference, estimation, and the structure of time.

Listed skills

  • Technical · Preferred
  • Organization · Preferred
  • Training · Preferred
  • Attention to detail · Preferred
  • staff · Preferred
  • Windows · Preferred
  • Time · Preferred
  • discipline · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

  • Mathematics
  • Physics
  • Computer Science
  • Statistical Inference
  • Estimation
  • Measurement
  • Deep Learning
  • World Models
  • Computational Neuroscience
  • Clinical Time Series
  • Longitudinal Clinical Data
  • Data Engineering
  • Research
  • System Building

Job areas

  • Technology
  • Science & Research
  • Data & Analytics
  • Healthcare
  • Software