Chaeyoung Kim
Senior Scientist @Eikon Therapeutics
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WORK HISTORY
Senior Scientist @Eikon Therapeutics
New York, NY, US
Owned end to end in vitro biology workstreams for CNS discovery programs, spanning assay design, execution, optimization, interpretation, and delivery of decision enabling datasets- Built imaging based cellular assays to quantify pathology relevant phenotypes and response to genetic or pharmacologic perturbations in neuronal systems- Systematically benchmarked iPSC derived and primary neuronal models to establish robust, reproducible conditions suitable for scaled experimentation- Partnered cross functionally with Engineering, Imaging, and Data Science to align experimental design, image acquisition, QC, and quantitative readouts- Applied Python based analysis workflows to QC imaging outputs, extract features, visualize trends, and streamline reporting to accelerate iteration cycles.
EDUCATION
Yonsei University
Master's degree, Molecular Biology
Seoul National University
Doctor of Philosophy - PhD, Neuroscience
ABOUT CHAEYOUNG KIM
Senior Scientist in CNS drug discovery and translational biology with hands on experience spanning human iPSC derived and primary neuronal models, target validation, and mechanism of action studies across oligonucleotide and small molecule programs.I build physiologically relevant in vitro and ex vivo platforms that connect directly to in vivo biology, integrating imaging, molecular, and functional assays to generate decision enabling datasets and clear go no go recommendations. My work includes single molecule tracking, high content imaging, and PK PD informed experimental design, supported by rigorous QC and quantitative analysis.I drive execution from experimental strategy through data delivery, partnering closely with in vivo pharmacology, chemistry, engineering, data science, and translational teams. I am recognized for combining deep bench level rigor with program level thinking, translating complex biology into crisp, actionable conclusions.I enjoy working at the interface of biology, technology, and data, especially where human relevant models and Python enabled analysis can de risk discovery and strengthen translational confidence.
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