Scientist, Computational Sensing
$115,000–$165,000 year
On-siteCambridge, Massachusetts, United States
Job Summary
Analyze nanopore and electrophysiology datasets to identify biologically meaningful signal features and develop computational workflows for event detection, classification, and molecular fingerprinting. Build quantitative models connecting measurements to molecular identity, structure, and function while collaborating with experimental scientists to interpret results and shape future experiments. Partner with protein science, signal processing, and machine learning teams to improve platform performance, establish benchmarking best practices, and transform complex data into actionable sequencing outputs. Work directly with diverse disciplines to define new analytical approaches for extracting rich molecular information from single-molecule interactions.
Required Qualifications
- Master's degree plus 3+ years of relevant industry experience, or PhD in Computational Biology, Biophysics, Bioengineering, Physics, Applied Mathematics, Computer Science, Electrical Engineering, or a related quantitative discipline
- Strong programming skills in Python and scientific computing environments
- Experience analyzing complex biological, physical, or time-series datasets — particularly in the presence of noise and experimental variability
- Solid background in at least two of: statistics, machine learning, signal processing, or Bayesian modeling
- Comfortable working across experimental and computational domains; able to engage meaningfully with wet-lab scientists on data interpretation
- Clear scientific communicator — written and verbal
Desired Qualifications
- Hands-on experience with nanopore technologies, electrophysiology, or single-molecule measurement platforms
- Experience applying deep learning or probabilistic modeling to biological or physical datasets
- Background in computational biophysics or time-series analysis of high-dimensional biological signals
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