Scientist, Computational Sensing

What you'll do

• Analyze nanopore and electrophysiology data to identify meaningful signal features and develop workflows for event detection, classification, and molecular fingerprinting.
• Build quantitative models connecting measurements to molecular identity, structure, and function; establish benchmarking, validation, and uncertainty-quantification practices.
• Collaborate with experimental scientists and cross-functional teams to interpret results and improve platform performance.

What they ask for

• Master's degree plus 3+ years of relevant industry experience, or a PhD in a listed or related quantitative discipline.
• Strong programming skills in Python and scientific computing environments.
• Experience analyzing complex biological, physical, or time-series datasets, including noisy or variable data.
• Background in at least two of statistics, machine learning, signal processing, or Bayesian modeling; ability to work across experimental and computational domains and communicate clearly.

Nice to have

• Hands-on experience with nanopore technologies, electrophysiology, or single-molecule measurement platforms.
• Experience applying deep learning or probabilistic modeling to biological or physical datasets; computational biophysics or high-dimensional biological time-series analysis.

Pay

$115,000 - $165,000 USD base salary

Tools

Python

AI focus

The role develops machine-learning-related analytical methods for biological sensing; the applicant privacy notice also states that applications may be reviewed using AI-assisted screening tools.