Skip to menu Skip to content Skip to footer
Dr Dharmesh Bhuva
Dr

Dharmesh Bhuva

Email: 

Overview

Background

Dr Dharmesh D Bhuva is a NHMRC Emerging Leadership Fellow (EL1) on a mission to understand how complex systems of gene regulation and signalling produce diverse tissue phenotypes in health, disease, and development. He completed his PhD in Oct 2020 through the Department of Mathematics and Statistics, University of Melbourne, focusing on developing novel systems biology approaches to study molecular function and gene regulation in cancer systems. His current work focuses on extending these ideas to biological tissues through the development of computational methods to generate accurate biological insights from spatial molecular datasets.

Whilst being an early career researcher, he has developed high quality bioinformatics software that have been downloaded more than 160,000 times, has received >$3.25M in funding support, including NHMRC and MRFF, and has published in Genome biology and Nucleic Acids Research, some of the highest-ranking journals in his field. Dr Bhuva has organised and run various computational biology workshops at the University of Melbourne as well as the WEHI Bioinformatics and Computational Biology Masterclass (2021) that was delivered to the Asia-Pacific region. He currently supervises a PhD student and has co-supervised 2 successful MSc Bioinformatics students.

Availability

Dr Dharmesh Bhuva is:
Available for supervision

Qualifications

  • Bachelor of Computer Science, University of Southampton
  • Masters (Coursework) of Bioinformatics, University of Melbourne
  • Doctor of Philosophy of Mathematics and Statistics, University of Melbourne
  • Honorary Fellow, University of Adelaide, University of Adelaide

Research impacts

Dr Bhuva is an expert in developing and implementing novel computational methods that have been widely used in the field to advance knowledge of disease systems. He is a well-rounded early career researcher who has led teams to develop innovative solutions to complex analytics problems that enhance biological insight from data.

Contributions to science: Bhuva has worked in the fields of computational and systems biology for over 5 years with a focus on developing approaches to decipher complex molecular phenotypes and the regulatory mechanisms from various cancer data types, including single-cell and spatial transcriptomics. His recent work highlighted a wide-spread issue with analysing spatial ‘omics datasets and resulted in recommended best practices to address it. He has disseminated his work through 28 conferences, seminar talks and workshops (14 invitations).

Supervision, mentoring and teaching: Bhuva has delivered guest workshops to the University of Melbourne masters students for 4 consecutive years. He has also been invited to deliver 6 workshops, including one international workshop. He has successfully supervised 2 MSc students that have gone on to PhDs and has mentored 2 PhD students in his lab. He is currently supervising a PhD student (2023-present).

Professional engagement: Bhuva is a member of the Australian Bioinformatics and Computational Biology Society (ABACBS). He was on the organising committee of the annual ABACBS conference (2022, Melbourne). He has helped organise the WEHI Bioinformatics and Computational masterclass (Online, 2021) that had attendees from 15 countries. He formed the post-doctoral committee at the newly established South Australian Immunogenomics Cancer Institute (SAiGENCI) and served on the committee from 2024-2025.

Works

Search Professor Dharmesh Bhuva’s works on UQ eSpace

21 works between 2018 and 2026

21 - 21 of 21 works

2018

Journal Article

Single sample scoring of molecular phenotypes

Foroutan, Momeneh, Bhuva, Dharmesh D., Lyu, Ruqian, Horan, Kristy, Cursons, Joseph and Davis, Melissa J. (2018). Single sample scoring of molecular phenotypes. BMC Bioinformatics, 19 (1) 404, 1-10. doi: 10.1186/s12859-018-2435-4

Single sample scoring of molecular phenotypes

Funding

Current funding

  • 2025 - 2029
    Studying the topology of cancer tissue and its microenvironment to identify topological biomarkers
    NHMRC Investigator Grants
    Open grant

Supervision

Availability

Dr Dharmesh Bhuva is:
Available for supervision

Looking for a supervisor? Read our advice on how to choose a supervisor.

Available projects

  • Spatial Phenotypic Plasticity and Therapy Resistance in Cancer

    Location

    Frazer Institute / Translational Research Institute University of Queensland, Brisbane, Australia

    Project Overview

    Therapy resistance remains one of the greatest challenges in cancer treatment. Increasing evidence suggests that spatial heterogeneity and phenotypic plasticity within tumours play a critical role in enabling cancer cells to evade therapy.

    This PhD project will use spatial transcriptomics and systems biology approaches to characterise how tumour cells dynamically adapt within their microenvironment, and how these adaptations contribute to treatment resistance.

    Research Aims

    • Characterise spatial heterogeneity in tumour tissues
    • Identify plastic cell states associated with therapy resistance
    • Map interactions between:
      • Tumour cells
      • Immune cells
      • Stromal components
    • Develop computational models to:
      • Track cellular state transitions
      • Predict resistance mechanisms
    • Integrate multi-omics data (transcriptomics, proteomics where available)

    Methodologies

    • Spatial transcriptomics and single-cell RNA-seq
    • Trajectory inference and cell-state modelling
    • Network and pathway analysis
    • Integration of multi-omics datasets
    • Development of reproducible computational pipelines

    Expected Outcomes

    • Identification of spatially defined resistant cell populations
    • New insights into tumour evolution and adaptation
    • Potential biomarkers for predicting treatment response
    • Publications in leading journals (e.g., Cancer Cell, Nature Communications)

    Candidate Requirements

    • Background in:
      • Bioinformatics / Computational Biology / Biomedical Science
    • Programming skills (R/Python preferred)
    • Strong interest in:
      • Cancer biology
      • Genomics and data analysis
    • Ability to work in an interdisciplinary environment

    Supervisory Team

    • Dr. Dharmesh Bhuva – Computational Biology, cancer genomics, spatial omics
    • Collaborative network with cancer researchers and clinicians

    Funding

    Scholarship opportunities available (RTP/UQ and external funding schemes).

    How to Apply

    Applicants should provide:

    • CV
    • Academic transcripts
    • Statement of interest outlining relevant experience
    • Referee contacts

Supervision history

Current supervision

Media

Enquiries

For media enquiries about Dr Dharmesh Bhuva's areas of expertise, story ideas and help finding experts, contact our Media team:

communications@uq.edu.au