Dr. Stephanie Gras

Associate Professor

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Biography

Stephanie Gras is an Associate Professor at Monash University with a rich background in immunology and the interactions between viruses and the immune system. Her work centers on understanding how the immune system recognizes and eliminates viral infections, specifically focusing on viruses that can mutate to escape this surveillance, such as HIV. Through her research, she has contributed significantly to vaccine development and therapeutic strategies addressing viral infections. Stephanie is actively involved in multiple research projects, including those that explore T cell responses in HIV controllers and the epigenetic regulation of immune memory. She has received several prestigious awards, including the ARC Future Fellowship and the Georgina Sweet Award for Women in Quantitative Biomedical Science, recognizing her contributions to the field. Furthermore, she has collaborated extensively on various projects aimed at improving our understanding of viral immunology and contributing to the Global Sustainable Development Goals.

Research Interests

Experience

Associate Professor

2011-01-01 — Present

Monash University • Melbourne

Associate Professor in the field of immunology, focusing on viral infections and immune system interactions.

Awards

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ARC Future Fellowship

2012-01-01
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Dean's Award Early Career

2011-01-01
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Georgina Sweet Award

2017-01-01

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.