Dr. Anderly Chueh

Assistant Professor

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Biography

Anderly Chueh is a Research Fellow at Monash University, specializing in cancer biomarker discovery and small molecule drug development. He completed his PhD in Professor KH Andy Choo’s laboratory at the Murdoch Children’s Research Institute, focusing on developing innovative genomic tiling PCR techniques for high-resolution detection of chromosomal aberrations in human patient samples. Following his PhD, Dr. Chueh undertook a Postdoctoral Fellowship at the Ludwig Institute of Cancer Research where he honed his skills in colon cancer cell biology and drug therapeutics. His notable work on histone deacetylase inhibitors led to the identification of a novel transcriptional axis that predicts drug sensitivity in tumors, contributing significantly to overcoming resistance. In 2013, he joined the Walter and Eliza Hall Institute and played a vital role in the biotech startup CTx CRC Limited, engaging in high-throughput drug screening and biomarker identification. Since 2019, he has been working in Professor Roger Daly's lab at Monash, applying advanced high-throughput screening technologies and mouse model tools for developing novel cancer therapies and companion biomarkers.

Research Interests

Experience

Research Fellow

2019-01-01 — Present

Monash University • Melbourne, Australia

Conducting research in cancer biomarker discovery and developing small molecule therapies.

Awards

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Outstanding Achievement - Industry Engagement Commercialisation Award

Requirements for Monash University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:6
Reading
Required:6
Writing
Required:6
Speaking
Required:6
Overall
Required:6.5
TOEFL
Listening
Required:12
Reading
Required:13
Writing
Required:21
Speaking
Required:18
Total
Required:79
Prerequisites
Bachelor degree (or equivalent) in a related field
Application Checklist
  • Academic Transcripts
  • Proof of English Proficiency
  • Curriculum Vitae
  • Copy of Passport
Specialization Notes

Requirements are standardized across the Faculty of Information Technology for most Master's programs including Computer Science and Data Science.