Dr. David Chalmers

Associate Professor

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Biography

David Chalmers is an Associate Professor at Monash University's Faculty of Pharmacy and Pharmaceutical Sciences, specializing in Medicinal Chemistry. His research focuses on the use of computational modeling methods to design new drugs and medicines. He employs techniques such as molecular dynamics simulations and molecular docking to understand the interactions between drugs and their receptors, working to formulate effective drug delivery systems, including tablets and capsules. His expertise also extends to applying artificial intelligence and machine learning in drug design, particularly in the area of peptide chemistry and anti-infective agents. Chalmers’ project collaborations include research on novel treatments for heart failure and Alzheimer’s disease, as well as methods targeting complex molecular mechanisms in GPCR signaling. His educational contributions include teaching courses on drug discovery design and computational drug design optimization. He is committed to advancing pharmaceutical sciences and aligning his research efforts with global sustainability goals, particularly through the development of innovative drug therapies.

Research Interests

Experience

Associate Professor

2001-01-01 — Present

Monash University • Melbourne, VIC

Teaching and researching in the field of Medicinal Chemistry, focusing on drug design and computational modeling.

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.