Dharmesh Bhuva
NHMRC Emerging Leadership Fellow (EL1) at UQ Frazer Institute
Queensland, Australia
Summary
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Senior🎓
Top SchoolDharmesh Bhuva is an NHMRC Emerging Leadership Fellow and cancer systems biology researcher with eight years’ experience in bioinformatics, spatial statistics, and network-based analysis of large-scale transcriptomic data, including single-cell and spatial technologies. He holds a PhD in Mathematics and Statistics and built three open-source software packages during his doctoral work, contributing to multiple peer-reviewed publications. Dharmesh has progressed from bioinformatics roles at WEHI to senior postdoctoral work at SAiGENCI and now leads systems biology efforts at the UQ Frazer Institute, bridging quantitative method development with translational cancer research. Known for thriving in multidisciplinary teams, he combines rigorous statistical training with practical software engineering to make complex genomic datasets interpretable for biology and medicine. A detail often overlooked: his background in First Class Honours Computer Science complements his statistics training, enabling end-to-end tool development from algorithm to implementation.
9 years of coding experience
2 years of employment as a software developer
SCLP Samaj SchoolBachelors of Science (BSc), Computer Science, First Class Honours, Bachelors of Science (BSc), Computer Science, First Class Honours at University of SouthamptonThe University of Melbourne
English, Gujarati, Hindi
Github Skills (22)
bioconductor10
bioinformatics10
spatial-transcriptomics8
network-analysis8
r-package8
proportions7
multilevel7
r6
hpc-cluster4
tidyverse4
random-effects4
bayesian4
database4
backend4
correlation3
Programming languages (5)
Github contributions (5)
DavisLaboratory/dcanr
Sep 2018 - Oct 2022
Differential co-expression/association network analysis
Contributions:112 commits, 2 PRs, 56 pushes in 4 years 1 month
co-expressiondifferentialnetwork-analysisassociation
DavisLaboratory/singscore
Oct 2018 - Oct 2022
An R/Bioconductor package that implements a single-sample molecular phenotyping approach
Contributions:84 commits, 6 PRs, 74 pushes in 4 years 1 month
bioconductorbioinformatics
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