ARC Research Hub for Medicinal Agriculture

ARC Research Hub for Medicinal Agriculture Graduate Research Scholarships

The ARC MedAg Hub is a multidisciplinary collaboration conducting pre-clinical research in medicinal agriculture amongst researchers at La Trobe University, The University of Melbourne, Olivia Newton-John Cancer Research Institute, in collaboration with funding agency the Australian Research Council and leading industry partners Cann Group Limited, Hexima, Photon Systems Instruments, SensaData, UTT BioPharma, Bio Platforms Australia and Palo Alto Research Center Inc. The Hub works to apply knowledge and leading-edge innovation by transforming high quality, plant-derived therapeutics production into an integrated industry spanning primary producers and manufacturers.

Currently, the ARC MedAg Hub is offering seven scholarships, amongst the nine projects advertised below, for outstanding PhD candidates to undertake research aimed at improving the profitability and sustainability of medicinal agriculture for primary producers and adding value for pharmaceutical manufacturers and end-users.

In addition to receiving a La Trobe Graduate Research/Research Training Program scholarship, scholarship recipients will have the opportunity to be involved in an innovative industry transformation hub involving outstanding researchers and industry partners.

Please note: these scholarships are open to Australian and New Zealand Citizens and Australian permanent residents only.

Eligibility

In addition to the standard eligibility requirements for La Trobe Graduate Research Scholarships, applicants must also meet the following criteria:

  • have an interest in subjects related to medicinal agriculture or plant biology, such as; breeding, genetics, high-throughput imaging and phenomics, genome regulation, metabolomics, integrative ‘omic analysis, biochemistry, secondary/specialized metabolism.
  • be an Australian and New Zealand citizen or Australian permanent resident

How to apply

Information on how to apply is available on our Graduate Research Scholarships page. To obtain in-principle agreement to apply, or for any other questions about the projects, please email medaghub@latrobe.edu.au.

Please also be aware that:

  • Due to the nature of the research involved, confidentiality and security criteria will need to be agreed to before offers can be secured.
  • Potential candidates may be required to be interviewed as part of the application process.
  • You must complete a Research Statement Form for each project you wish to be considered for. While you may apply for multiple projects, only one scholarship will be awarded per candidate.

More information

For further information about these scholarships or to discuss your suitability, visit the ARC MedAG Hub website, or email medaghub@latrobe.edu.au

Current available research projects

Cannabis Flowering

Background

Medicinal compounds in cannabis are primarily produced in flowers. The time of flowering is important for both the amount of floral material produced and how many harvests can be collected in a year, yet we know relatively little about how this process is regulated in cannabis. This project will identify regulators of flowering time and investigate pathways to generate cannabis varieties with optimised flowering behaviour.

Structural genomics of cannabis enzymes

Background

Despite being the foundation of a multi-billion-dollar global industry, scientific knowledge and research on cannabis is lagging compared to other high-value crops. The most valuable cannabis product today is the terpene- and cannabinoid-rich resin with its various psychoactive and medicinal properties yet there is very little is known about the structure and function the enzymes that synthesis these compounds. This project will use structural genomics to define the structure and function of terpene synthases and O-methyltransferases involved in producing the unique medical properties of cannabis.

A multi-omics atlas of cannabis tissues

Background

Accurate regulatory models allow complex systems to be understood and key functional components to be predicted a priori. This project will generate a multi-omic atlas of cannabis tissues that encompasses transcript, proteomic, phosphoproteomic and orfeomic data. It will then explain the differing activity of specialized metabolism between tissues by generating predictive regulatory models and wet-bench testable hypotheses.

Is transcriptional regulation of specialized metabolism conserved across diverse species?

Background

Plants produce thousands of specialized metabolites as an adaptation to interacting with their environment. These compounds vary widely between plant species, highly dependent on their biological function and the specific challenges faced by the plant species. Transcriptional regulation of the pathways synthesising specialized metabolites is thought to be dominated by MYB and bHLH transcription factors, but has been well characterized in very few species. This project will make use of the recent wealth of genomic and transcriptomic data across a wide range of species to predict then validate the role of master regulatory transcription factors, assessing the degree of functional conservation across distantly related species.

Manipulation of cannabinoid production in cannabis

Background

Food, spinnable fibre as well as valuable secondary metabolites are derived from cannabis. This project will reveal the molecular mechanisms by which carbon partitioning into various organs and chemical components is regulated during plant growth and development.

Development of Solvent Extraction Technologies for the Selective Extraction of Cannabinoids and Terpenes

Background

Development of effective and efficient separation technologies for cannabis extraction is key to the widespread deployment of cannabis derived products for medicinal purposes. This project will develop liquid-liquid separation processes to achieve this goal using tools including thermodynamic software packages such as COSMO-SAC, in combination with laboratory and pilot plant trials.

Healthy plants for human health: tackling plant disease in medicinal cannabis production

Background

Diseases can reduce yield and contaminate medicinal cannabis products with pathogens and agrichemicals. This project aims to control fungal diseases without the use of agrichemicals. The project aims to develop surveillance techniques for early warning of pathogen presence, enabling timely interventions. It will determine whether metabolite engineering of cannabis affects natural disease resistance.

Prediction and evaluation of plant traits through the application of machine learning algorithms on hyperspectral phenomics imaging data

Background

With the establishment of the large-scale phenotyping capacity at La Trobe University, an abundance of imaging data is expected to be generated using RGB, thermal, fluorescent and hyperspectral imaging systems. Compared to other imaging techniques, a hyperspectral approach substantially increases data size as well as the complexity of evaluation. It becomes increasingly difficult for humans, even with sophisticated data processing algorithms, to synthesise information in order to successfully predict plant trait trends. This project aims to investigate and augment the latest research in neural networks/machine learning algorithms to better predict plant development and evaluate plant traits based on the visible and near-infrared hyperspectral data.

Micro-climate modelling of in-door growing conditions of medicinal crops using sensor fusion

Background

The yield and potency of medicinal agriculture crops can be affected by the microclimate of individual plants within indoor cultivation practices. The research will involve undertaking targeted research to develop microclimate modelling using sensor fusion and developing a complimentary expert systems model for use in real-time monitoring and control systems of desired growing conditions. The work will include integration of sensor systems developed by our Hub partners SensaData and PSI, and subsequent development of computation models for microclimate that are co-developed in collaboration with agricultural scientists.