Summary
Mayur Divate is a bioinformatics engineer and final-year PhD with 11 years of experience applying computational methods to cancer and NGS data. During his PhD at QUT he developed deep learning models to identify pan-cancer gene expression signatures, then translated those models to nominate cell-surface and secreted protein markers and to infer origins of cancers of unknown primary via transfer learning. He brings hands-on production experience from Agilent in variant calling, annotation and cloud-enabled pipelines (Python, SQL, AWS, APIs) alongside a strong research background in ATAC-seq, ChIP-seq and single-cell RNA-seq. Comfortable across Python, R and Java, he has a track record of building tools and pipelines (including the GUAVA ATAC-seq tool) and operationalizing analyses for research and industry. Based in Queensland, Australia, he is seeking roles in data science, Python development or postdoctoral bioinformatics where he can bridge algorithm development and applied genomics. Colleagues would describe him as someone who moves seamlessly between exploratory research and production-grade bioinformatics solutions.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Bioinformatics, Doctor of Philosophy - PhD, Bioinformatics at QUT (Queensland University of Technology)
Master of Science (MSc), Bioinformatics, A, Master of Science (MSc), Bioinformatics, A at Savitribai Phule Pune University
Hindi, Marathi, English