Dr. Liana Pozza

Instructor

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Biography

Liana Pozza is a Lecturer in Agricultural Data Science at the University of Sydney's School of Life and Environmental Sciences. Her research interests focus on pedagogy and environmental modeling, specifically understanding spatial distribution of soil properties and the constraints of cropping and soil contaminants. She is actively involved in teaching applied statistics and environmental GIS units and has a robust experience in teaching soil science through field-based agricultural units. Her specific research revolves around modeling, sample design, spatial analysis, and their applicability in agricultural contexts. Additionally, Liana is engaged in pedagogical research aimed at enhancing the student experience, particularly in group work and the exploration of AI in assessment feedback. Notable projects she has contributed to include the prediction of soil properties affecting crop yields, soil carbon monitoring methods, and interdisciplinary learning initiatives in undergraduate units.

Research Interests

Experience

Lecturer in Agricultural Data Science

2015-01-01 — Present

University of Sydney • Sydney, Australia

Teaching applied statistics and GIS units; conducting research in soil and agricultural contexts.

Awards

#

AgData Challenge Hackathon Prize

2022-01-01

Courses

Introductory Statistical Methods Applied Statistical Methods Global Challenges: Food, Water, Climate

Requirements for University of Sydney

Doctorate Program
Requirements
GPA Requirement
Required:3.3
IELTS
Listening
Required:6
Reading
Required:6
Writing
Required:6
Speaking
Required:6
Overall
Required:6.5
TOEFL
Listening
Required:17
Reading
Required:17
Writing
Required:19
Speaking
Required:17
Total
Required:85
PTE
Listening
Required:54
Reading
Required:54
Writing
Required:54
Speaking
Required:54
Overall
Required:61
Prerequisites
A master's degree with a research component or a bachelor's degree with first or second-class honours. Demonstrated research experience and capability.
Application Checklist
  • Academic transcripts
  • Curriculum Vitae (CV)
  • Research proposal (1000+ words)
  • Two academic referee reports
  • Evidence of residency status
  • Written statement of support from potential supervisor
Specialization Notes

This entry applies to Faculty of Science PhD programs including Departments such as Life and Environmental Sciences, Physics, Chemistry, and Mathematics and Statistics.