About Evident Digital Pathology
Evident Scientific, formerly part of Olympus Corporation, is a global leader in life-science microscopy and optical instrumentation. Following the recent acquisition of Pramana, a pioneer in Autonomous Digital Imaging, Evident has combined its world-class optical heritage with Pramana’s software, robotics, and AI innovation to define the future of Digital Pathology.
Our young, high-performing engineering team has already taken the industry to its next node in autonomy—building the world’s most advanced whole-slide imaging platform, deployed at the Mayo Clinic to create the world’s largest digital pathology archive. Today, this technology is trusted by more than 30 top-tier medical institutions across the U.S. and Europe, powering Clinical workflows directly aiding in patient care.
As part of Evident, this team is now advancing to the next level of autonomy—moving from autonomous imaging to intelligent imaging, where scanners, data systems, and user interfaces are self-aware, adaptive, and capable of real-time AI inference at the edge.
We are looking for a highly motivated Digital Imaging Intern to join our Digital Imaging team. This internship offers a unique opportunity to gain hands-on experience in the development of cutting-edge imaging algorithms and contribute to real-world applications in digital pathology and computer vision.
Responsibilities:
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Assist in the research and development of imaging algorithms for tasks such as image segmentation, classification, and enhancement.
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Support ongoing projects related to whole slide imaging (WSI) and tissue specimen analysis.
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Experiment with colour space transformations (e.g., RGB, HSV) to improve image processing workflows.
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Collaborate with the image quality evaluation team to test and refine algorithm performance.
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Help build and test models for optimizing imaging parameters and sequences based on specimen content.
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Work with software and platform engineers to support the integration of algorithms into software pipelines.
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Contribute to documentation, testing, and validation of imaging solutions.
Requirements:
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Basic understanding of image processing concepts such as segmentation, classification, color spaces, and image quality assessment.
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Foundational knowledge of mathematics, including probability, algebra, and calculus.
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Experience with programming in Python and/or C/C++.
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Familiarity with image processing libraries (e.g., OpenCV, PIL) or machine learning frameworks (e.g., TensorFlow, PyTorch) is a plus.
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Interest in imaging systems, sensor technologies, or medical image analysis.
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Strong analytical thinking, problem-solving skills, and attention to detail.
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Eagerness to learn and contribute to a collaborative research and development environment.
Bonus Qualifications (Nice to Have):
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Coursework or project experience in computer vision, optics, or deep learning.
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Familiarity with neural networks, graphics tools, or compute engines used in ML/CV.
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Previous research or internship experience related to image analysis or digital imaging.
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Contributions to publications, open-source projects, or hackathons.
