Graduate Student and Postdoctoral Researcher Positions Available
Stem Cell, Organoid Imaging, and AI Biology

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The Yoon Laboratory at KAIST is seeking highly motivated graduate students and postdoctoral researchers who are interested in interdisciplinary research at the interface of stem cell biology, organoid models, high-resolution live imaging, and AI-driven biological analysis.

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Our lab aims to develop next-generation experimental and computational platforms to understand dynamic cellular states in stem cells and organoids. We are particularly interested in using label-free, high-resolution, real-time imaging approaches combined with deep learning to analyze cellular morphology, organelle dynamics, differentiation trajectories, disease phenotypes, and drug responses.

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One example of our ongoing research direction is the development of deep learning-guided holotomography-based platforms for monitoring early structural changes during human pluripotent stem cell differentiation.

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https://www.biorxiv.org/content/10.64898/2026.04.23.720508v1 

 

Through this type of approach, we aim to build AI-powered imaging systems that can quantitatively evaluate stem cell and organoid states without destructive staining or endpoint assays.

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We welcome applicants with backgrounds in biology, stem cell biology, neuroscience, bioengineering, computer science, applied mathematics, bioinformatics, computational biology, imaging, or related fields. Prior experience in one or more of the following areas will be considered a strong advantage:

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• stem cell or organoid culture

• live-cell imaging or high-resolution microscopy

• holotomography, confocal microscopy, or other quantitative imaging platforms

• image analysis and computer vision

• machine learning or deep learning

• bioinformatics or computational biology

• mathematical modeling or quantitative biology

• programming experience in Python, R, MATLAB, or related languages

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Candidates do not need to have expertise in all areas. We are especially interested in applicants who are eager to work across disciplinary boundaries and learn both experimental and computational approaches.

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Successful candidates will have the opportunity to participate in projects involving AI-based analysis of stem cell and organoid imaging data, development of quantitative phenotyping platforms, disease modeling using human pluripotent stem cell-derived systems, and drug response prediction using advanced organoid models.

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Interested applicants should send a CV, a brief statement of research interests to Ki-Jun Yoon (kijunyoon@kaist.ac.kr).

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