Topics in optimal experimental design

Study level


Master of Philosophy


Vacation research experience scheme

Topic status

We're looking for students to study this topic.


Associate Professor James McGree
Associate Professor in Statistics
Division / Faculty
Science and Engineering Faculty
Dr Erin Peterson
Principal Research Fellow
Division / Faculty
Science and Engineering Faculty


Research in science and technology can be a process of guided learning through experiments.

The purpose of experimental design is to make that process as efficient as possible.

In this project, you will develop innovative and novel methods in statistics to answer open research questions in, for example, biology, agriculture and medicine.

Potential topics include:

  • New computational algorithms for adaptive N-of-1 clinical trials.
  • Experimental design methods for precision agriculture.
  • Preventing the spread of infectious diseases through designed experiments.
  • Understanding tumour growth through new experiments in biology.
  • New experimental design methods for efficiently monitoring the Great Barrier Reef.
  • Determining optimal flight paths for drones through designed experiments.
  • Real-time control of nonlinear dynamical systems with designed experiments.
  • Facilitating efficient inference of big data using designed experiments.
  • Optimisation of noisy, high dimensional and computationally expensive utility functions.
  • How to run globally distributed experiments: A case study in plant ecology.

Research activities

In this project, you will

  • understand real-world problems that motivate research in statistics
  • develop new statistical and/or computational methods to solve real-world problems
  • develop high performance computing skills
  • work within an active, successful and diverse research group.


The aim of this project is to develop new statistical and/or computational methods to design real-world experiments.

The expected outcomes include advancing fields such as agriculture, health and marine science through applying new methods to run new experiments and capture data.

This will potentially lead to publications in a high quality statistics and/or applied journals.

Skills and experience

Criteria is different depending on your study level:

  • VRES students: You must be enrolled in the statistics major.
  • Honours/Masters: You must have completed a Bachelors degree (or equivalent) in statistics or a related field.
  • PhD: You must have completed a Honours/Masters (or equivalent) in statistics or a related field.


You may be able to apply for a research scholarship in our annual scholarship round.

Annual scholarship round



Contact the supervisor for more information.