2022 HDR Scholarship – Next-generation soil spectroscopic modelling with explainable machine learning

Eligible courses

HDR student interested in soil science research and in the application of mathematical and statistical methods.

Eligibility criteria

Applicants must hold a First or Upper Second-Class Bachelor's degree, or an M.Sc. degree in a related science field (soil science, ecology, agriculture, environment---with emphasis in the application of mathematical and statistical methods), with a Merit and a minimum average grade of 65% and substantial research component.
Applicants must be driven and determined to successfully undertake a higher degree program. They must possess ability and confidence to self-manage and execute tasks individually, work well under supervision, be open to feedback and input from others, and ability to collaborate, negotiate, influence, and inspire others.
Applicants must demonstrate:

good understanding of modern, quantitative methods in soil science, especially spectroscopy, multivariate statistical modelling and machine learning including neural networks and deep learning,
strong aptitude for statistical programming, for example using R, Python,
fundamental understanding of linear algebra, calculus, and statistics,
excellent written and communication skills, and
disposition for scientific communication, writing and publication.