Computational Imaging Engineer

Ramona Optics•Durham, NC

About The Position

Our MCAM™ platform moves across 9 axes of motion and 5 distinct magnifications, and our users expect the same image quality at NA=0.05 as they do at NA=0.3. Delivering on that promise means treating calibration not as a one-time setup step, but as a rigorous, systematic, and continuously verifiable part of the system itself — one that can scale to support a growing and increasingly diverse list of sample types and use cases. We are looking for a Computational Imaging Engineer to help us close the gap between the physics of image formation and the images our instruments actually produce. You will work at the intersection of optics, mechatronics, computer vision, and optical systems modeling, tackling questions like: what are the optical properties of the material a user places under the microscope, and can we assume those properties are constant? How do motion-system accuracy and vibration propagate into image blur? How do we separate signal from sensor noise, background, and illumination non-uniformity in a way that holds up across magnifications and sample types? This is a role for someone who enjoys grounding computer vision and image processing work in the underlying physics and mathematics of the imaging system, and who wants to build the calibration infrastructure that makes our instruments reliable, reproducible, and capable of growing with the science.

Requirements

Bachelor's or Master's degree in Optical Engineering, Physics, Electrical Engineering, or a related field (or equivalent experience).
2+ years of experience.
Strong foundation in the mathematics and physics underlying image formation, including Fourier optics, signal processing, and linear algebra.
Hands-on experience with image deconvolution, deblurring, or related inverse-problem techniques.
Experience characterizing noise, background, or illumination effects in optical or imaging systems.
Experience with geometric or optical calibration of imaging or measurement systems.
Strong proficiency in Python (or similar) for scientific computing and image processing.
Familiarity with how mechanical accuracy, vibration, or motion-system behavior affects image quality.
Strong problem-solving skills, attention to detail, and scientific curiosity.
Ability to communicate clearly and collaborate across disciplines spanning optics, mechatronics, and software.
Experience with computer vision techniques relevant to image registration, restoration, or quantitative analysis.

Nice To Haves

Master's or Ph.D. degree in Optics, Physics, or a closely related field.
5+ years of experience.
Experience with optical systems modeling or simulation tools.
Experience working on multi-axis or multi-magnification imaging instruments.

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.