Dr. David Balding

Professor

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Biography

Since completing my PhD, I have focused on developing and applying statistical and computational methods in genetics and related biological fields. My work encompasses areas such as population, evolutionary, and forensic genetics, with significant contributions to the interpretation of DNA profiles through match probability formulae, including coancestry coefficients known as the 'Balding-Nichols formulae'. I have worked on various aspects of evidence interpretation and statistical genetics, particularly concerning low template and degraded DNA profiles, as exemplified by my development of the likeLTD software. My research has led to foundational work in Approximate Bayesian Computation and demographics modeling within population genetics, contributing to the understanding of genetic ancestry through tools designed to analyze Y-chromosome data. Additionally, I have written numerous review articles that focus on cutting-edge statistical methods within genetic association studies and population structure analysis. Overall, my scholarly output comprises a blend of theoretical advancements and practical applications aimed at enhancing the understanding of complex genetic traits and ancestries.

Research Interests

Requirements for University of Melbourne

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:16
Reading
Required:16
Writing
Required:19
Speaking
Required:19
Total
Required:81
PTE
Listening
Required:60
Reading
Required:60
Writing
Required:60
Speaking
Required:60
Overall
Required:64
Prerequisites
Undergraduate degree in a cognate discipline (Computer Science, Data Science, or Statistics) MAST10006 Calculus 2 MAST10007 Linear Algebra At least 12.5 credit points of computer programming subjects
Application Checklist
  • Academic Transcripts
  • Graduation Certificate
  • Evidence of English Proficiency
  • CV/Resume
  • Statement of Purpose