NTHRYS › Internships › Ai Cancer Biology › Machine Learning Cancer Biomarker Discovery Pipeline

Active Learning and Uncertainty Quantification for Optimal Biomarker Sampling

Ai Cancer Biology

Machine Learning Cancer Biomarker Discovery Pipeline

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Ai Cancer Biology › Machine Learning Cancer Biomarker Discovery Pipeline

Active Learning and Uncertainty Quantification for Optimal Biomarker Sampling

This investigation applies Bayesian uncertainty estimation and active learning algorithms to prioritize which patient samples should be sequenced or analyzed to maximize biomarker discovery efficiency. The work reduces experimental costs and time-to-biomarker by intelligently selecting informative samples.

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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

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