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La Trobe University is committed to delivering distinctive and high-quality degrees that incorporate the needs of businesses and future employers for medicinal agriculture. The recently established AgriBusiness degree is an example of La Trobe’s leadership in this area.
The ARC MedAg Hub recognises the importance of investing in education and training that prepares graduates for a range of careers in industry, from both the perspective of students and employers. This underpins the ARC MedAg Hub’s Capacity Building Platform’s key goal: to enhance industry human capital by developing, co-ordinating and delivering new courses focused directly on challenges faced by the medicinal agriculture industry.
ARC Research Hub for Medicinal Agriculture PhD Scholarships.
Please note: apart for the scholarship for Project 'Prediction and evaluation of plant traits through the application of machine learning algorithms on hyperspectral phenomics imaging data’ these scholarships are open to Australian and New Zealand Citizens and Australian permanent residents only.
$28,597 p/a for 3.5 years. Fee relief additional.
- Healthy plants for human health: tackling plant disease in medicinal cannabis production.
- Selective liquid-liquid solvent extraction of therapeutically active cannabinoids and terpenes from cannabis.
- Identification of novel antimicrobials from plants using a silkworm infection model.
- A multi-omics atlas of cannabis tissues.
- Is transcriptional regulation of specialized metabolism conserved across diverse species?
- Prediction and evaluation of plant traits through the application of machine learning algorithms on hyperspectral phenomics imaging data.
- Micro-climate modelling of in-door growing conditions of medicinal crops using sensor fusion.
The ARC Research Hub for Medicinal Agriculture (ARC MedAg 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. 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 ARC MedAg Hub is offering PhD Research Scholarships for outstanding, high achieving and motivated 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. Applicants should 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.
Benefits of the Scholarship:
- • a La Trobe Research Scholarship for three and a half years, with a value of $28,597.00 per annum, to support your living costs (2021 rate)
- • a fee-relief scholarship for up to four years to undertake a PhD at La Trobe University
- • opportunities to work with La Trobe’s outstanding researchers, and have access to our suite of professional development programs.
- • opportunity to be involved in an innovative industry transformation hub involving industry partners
To be eligible to apply for this scholarship, applicants must:
- • a Masters by research degree in a relevant discipline completed within the last ten years assessed at a La Trobe Masters by research standard of 75 or above;
- • an Honours degree, Masters by coursework or ungraded Masters by research degree completed within the last ten years where you achieved a weighted average mark of 70 or above across any coursework subjects; AND any of the following assessed at a La Trobe Masters by research standard of 75 or above:
- a research thesis of approximately 15,000-20,000 words; or - the degree includes a written research component comprising at least 3/8 of one year; or - you are the lead author of a peer-reviewed publication or other research published within the last ten years
How to Apply:
If you wish to apply for an ARC MedAg Hub PhD Scholarship, follow these steps:
- • Please contact the ARC MedAg Hub at firstname.lastname@example.org for any further details about the projects and your suitability.
- • When you received in-principle agreement for supervision, complete and submit your application to the La Trobe Graduate Research School by 30 April 2021 for admission into La Trobe’s PhD program, indicating for which ARC MedAg Hub PhD Scholarship program you wish to be considered.
- • The University will carefully review your application and consider you for these scholarships.
- • It is anticipated that the successful applicants will commence candidature in Semester 2, 2021.
- • Be an Australian and New Zealand citizen or Australian permanent resident for all projects with the exception of Project - Prediction and evaluation of plant traits through the application of machine learning algorithms on hyperspectral phenomics imaging data.
- • While you may express interest in being considered for one or more of these scholarships.
- • Candidates may be required to be interviewed as part of the application process.
- • Due to the nature of the research involved, confidential and security criteria will need to be agreed to before offers can be secured.
Who to contact for further information: For further information about these scholarships or to discuss your suitability, please email email@example.com.
- 1. Healthy plants for human health: tackling plant disease in medicinal cannabis production.
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 as well as developing surveillance techniques for early warning of pathogen presence, enabling timely interventions. It will determine whether metabolite engineering of cannabis affects natural disease resistance. The position will be based mainly in Narrabri, NSW and will work closely with cannabis industry representatives.
Special conditions Preference will be given to graduates with a strong background in/experience with fungal plant pathology.
- 2. Selective liquid-liquid solvent extraction of therapeutically active cannabinoids and terpenes from cannabis.
The therapeutic application of cannabinoids and terpenes derived from Cannabis sativa is playing an increasingly significant role in public health and medicine. Cannabis has been described as a veritable ‘treasure trove’, producing more than 100 different cannabinoids and terpenes. This project investigates a liquid-liquid solvent extraction process for the recovery of cannabinoids and terpenes from cannabis plant residues and unwanted impurities that offers a much more cost-effective separation solution over the standard supercritical CO2 extraction, which is characterised by high capital inputs and operating costs. The project involves the evaluation of a range of green solvents and extractants as well as the physical conditions of the separation process in the recovery efficiency of cannabinoids and terpenes. In collaboration with the Australian Research Council and industry partners, the project aims to deliver novel cannabis extraction methods into the pharmaceutical market and drive better outcomes in public health.
Special conditions This scholarship is only available to domestic applicants with a Bachelor Degree in chemistry or chemical engineering.
- 3. Identification of novel antimicrobials from plants using a silkworm infection model.
Essential oils (EOs) are secondary metabolites of plants, obtained by distillation or mechanical processes. Their composition varies not only on the basis of the different botanical species, but also on the part of plants used, the season of harvest, the environmental conditions, and the extraction techniques. Many compounds show marked antimicrobial activity, which makes them promising candidates for novel drugs to treat bacterial and fungal infections. However, in veterinary applications, data concerning both the in vitro susceptibility testing and the in vivo application of EOs for treatments is limited. To increase our discovery of novel antimicrobials from EO will take advantage of silkworm infection model. The silkworm infection model is a suitable model to examine the therapeutic effectiveness of antimicrobial agents as it has conserved immune response. similar pharmacokinetics compared to mammals and no ethical concerns. Will investigate the use of several different EOs extracts against a range of veterinary clinically significant bacteria and fungal pathogens using silkworm mode.
- 4. A multi-omics atlas of cannabis tissues.
Models allow complex systems to be tested and understood. By finding both regulatory genes and their targets within a biological system we can predict their function in plants (Nature Plants paper). This approach can be used to discover new genes that control traits like growth and yield, and the knowledge applied in biotechnology to improve plant performance. In this project we will generate a multi-omic atlas of cannabis tissues that maps transcript, proteomic, phosphoproteomic and orfeomic data. We will then use the atlas to describe the differing activity of specialized metabolism between cannabis tissues by generating predictive regulatory models and testing them in the lab. Students will get hands-on experience of a range of lab ‘omics techniques. They do not need to know bioinformatics - they will be trained in a range of integrative data analysis approaches that allow big data to be explored and understood. These skills would equip students very well for future employment in agricultural biotech or genomics.
- 5. Is transcriptional regulation of specialized metabolism conserved across diverse species?
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. The pathways synthesising specialized metabolites are under transcriptional regulation that appears to be dominated by MYB and bHLH transcription factors. However, transcriptional regulation of specialized metabolism has been characterized in very few species. This project will take both lab and bioinformatic approaches to understand how specialized metabolism is regulated in cannabis, opium poppies and many other species (New Phytologist review). It will make use of the recent wealth of genomic and transcriptomic data across a wide range of species (such as the 10k Plants project) to predict then validate the role of master regulatory transcription factors, assessing the degree of functional conservation across distantly related species. Students do not need to know bioinformatics already, but they will get the opportunity to learn this and a range of lab genomic techniques.
- 6. Prediction and evaluation of plant traits through the application of machine learning algorithms on hyperspectral phenomics imaging data.
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.
- 7. Micro-climate modelling of in-door growing conditions of medicinal crops using sensor fusion.
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.
Special condition: The PhD candidate will need to have a background in either Electronic Engineering or Computer Science.