Dr. Meiling Han

Professor

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Biography

Meiling Han is the Head of the Antibiotic Resistance Bacterial Metabolism Group at the Monash Biomedicine Discovery Institute, Monash University. She obtained her PhD in antimicrobial pharmacology from the Monash Institute of Pharmaceutical Science in 2018. Her research investigates how bacteria remodel their lipid metabolism to survive antibiotic stress and host immune responses. Dr. Han leads an independent, multidisciplinary research team that integrates molecular microbiology, systems pharmacology, and analytical chemistry, particularly antimicrobial metabolomics and membrane lipidomics. Her focus is on discovering novel therapeutic strategies that target lipid-associated resistance, addressing the global challenge of antimicrobial resistance. With over seven years of post-PhD experience, she has published more than 60 peer-reviewed papers in top journals including Nature Communications and Nature Microbiology, and has secured over AU$ 3 million in competitive funding, including the ARC DECRA Fellowship for 2023-2026.

Research Interests

Experience

Research Fellow

2018-01-01 — Present

Monash University • Melbourne, VIC

Leading independent research focused on bacterial metabolism and antibiotic resistance.

Awards

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ARC DECRA Fellowship

2022-09-01
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ASM Microbe Student Postdoctoral Travel Award

2016-01-01
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BDI Research Accelerator Program

2023-06-01
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Faculty Bridging Postdoctoral Fellowship

2018-01-01
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FMNHS Early Career Researcher Travel Grants

2022-01-01

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.