Scientist, Computational Sensing

Role: Bioinformatics Scientist developing computational methods to analyze nanopore and electrophysiology datasets, translating complex molecular measurements into biological insights. Responsibilities: create and implement data analysis pipelines for event detection, molecular fingerprinting, and signal classification; build models linking measurements to molecular identity, structure, and function; collaborate with experimental scientists and cross-disciplinary teams to interpret data and improve platform performance; establish validation and benchmarking practices. Requirements: Master's degree with 3+ years industry experience or PhD in Computational Biology, Biophysics, Bioengineering, or related field; proficiency in Python and scientific computing; experience analyzing noisy biological or physical time-series data; strong background in statistics, machine learning, signal processing, or Bayesian modeling; ability to work across experimental and computational domains; effective scientific communicator. Preferred: hands-on nanopore or single-molecule tech experience; deep learning or probabilistic modeling skills; background in computational biophysics or high-dimensional time-series analysis. High-Value: focus on biological sensing, signal processing, and data modeling at the intersection of biology, physics, and machine learning, with emphasis on developing new analytical frameworks for nanopore measurements. Work setup: not specified.