Job Description

Job Overview

We're looking for someone who enjoys working with messy, real-world data and who solves problems by thinking, not by pasting keywords into a model zoo. We analyze individual seeds using proprietary hardware, and predict which ones will grow into strong plants. Your role is to help turn raw measurements into something reliable, interpretable, and useful for growers who depend on every seed.

You'll fit well here if you have a solid foundation in mathematics or statistics, or a STEM background with advanced training where you actually applied algorithms, not just read about them. This work involves building and maintaining the flow of data from the scanner, through our processing steps, into models that behave predictably. If you like questions where the data looks strange, the labels are imperfect, and the correct solution is not in a textbook, you'll probably enjoy this.

Responsibilities

Connect information from our seed scanner to the outcomes we see later in the greenhouse. Help shape and maintain the flow of data through our system. Build approaches that allow us to make reliable, real-time predictions from imperfect, biological data. Work with the team to refine how we store, process, and understand seed-level information.

Experience

A background in mathematics, statistics, physics, engineering, or another field where quantitative reasoning is central. Advanced training (Master's or PhD) focused on actually applying analytical methods, not just completing programming coursework. Comfortable writing your own code to explore unfamiliar data, rather than relying on tutorials or pre-packaged solutions. Experience working with real, imperfect data where there is no "correct pipeline" or standard textbook answer. Evidence that you can think independently and design your own approach when given a messy problem.

Eligibility

This position is funded through the IRAP Youth Employment Program.
To apply, you must meet the federal IRAP criteria. This is an immediate hire. We will contact candidates who meet the requirements and follow the application instructions.

This position is in person on campus at the University of British Columbia. Applicants MUST apply to

hrinsporos@gmail.com

with cover letter and resume; please also tell us about your favourite fruit or vegetable.
Job Type: Full-time

Pay: $60,000.00-$65,000.00 per year

Benefits:

Employee stock purchase plan
Work Location: In person