Computational Imaging Engineer

Ramona is reimagining microscopy for modern biology with their innovative Multi-Camera Array Microscope (MCAM™). They are seeking a Computational Imaging Engineer to develop calibration procedures and improve image quality through rigorous modeling and correction techniques.

Responsibilities:

• Develop rigorous, systematic, and mathematically grounded calibration procedures for multi-axis, multi-magnification optical instruments
• Characterize sensor and image noise sources and build models to quantify and correct for them
• Model and correct optical and geometric image deformations introduced by the imaging system
• Design and implement high-performance deconvolution algorithms to recover image detail across a range of numerical apertures
• Develop methods for background estimation, source characterization, and background subtraction in microscopy images
• Characterize how motion-system accuracy and mechanical vibration affect image formation, and develop approaches to mitigate their impact
• Characterize illumination sources and their contribution to image quality, and develop correction strategies
• Characterize fluorescence imaging performance — including excitation/emission behavior, photobleaching, spectral crosstalk, and signal-to-background ratio — across magnifications and sample types, as a critical input to system calibration
• Investigate the optical properties of diverse sample materials and assess their variability, building this understanding into the system's calibration and analysis pipelines
• Translate optical systems models and computer vision techniques into robust, production-ready software that integrates with the broader imaging platform
• Collaborate closely with optics, mechatronics, and software engineers to validate calibration approaches against real instrument behavior
• Document calibration methodologies, models, and validation procedures for internal and external use
• Evaluate and adopt emerging techniques in computational imaging, optical systems modeling, and computer vision to improve calibration accuracy and scalability