Centre for Nutrition and Food Science - Winter Research Programs 2026 Projects
General information on the program, including how to apply, is available from the UQ Student Employability Centre’s program website.
Physical, functional and sensory properties of sorghum grains and products
Primary Supervisor: Dr Jaqueline Moura Nadolny | j.mouranadolny@uq.edu.au
Please contact Dr Jaqui (j.mouranadolny@uq.edu.au) before submitting an application.
Duration: 4 weeks (30 hours per week); On-site
Location: Long Pocket
The project will investigate the functional properties of sorghum through targeted laboratory work, rapid consumer insight testing, and a review of supply‑chain opportunities. It will explore how processing influences sorghum’s performance in food applications and how consumers perceive sorghum‑based products. Findings will inform practical recommendations for industry adoption and value‑chain development.
Expected outcomes: The student will gain experience on the properties of grains, flours and food products made with them (functional, physical, processing, sensory). Also knowledge on consumer insights and novel comercial propertus.
Suitability: This project is suitable for 3rd–4th year undergraduate and master’s students with a background in mainly in food processing, but also sensory and food science.
Developing the Australian high-quality vanilla extract through the novel enzymatic approach
Primary Supervisors:
Dr Benny Yang | beichen.yang@uq.edu.au
Prof Heather Smyth | h.smyth@uq.edu.au
Please contact Dr Benny Yang (beichen.yang@uq.edu.au) or Prof Heather Smyth (h.smyth@uq.edu.au) before applying.
Duration: 4 weeks (30 hours per week); onsite
Location: Long Pocket
Traditional vanilla curing is a slow and labour-intensive process that typically requires several months to transform green vanilla beans into market-ready products. This project aims to develop a rapid, controlled curing strategy capable of producing high-quality vanilla extract within days by optimising environmental conditions and targeted enzymatic treatments. Preliminary laboratory trials have identified promising parameters that significantly accelerate flavour development while maintaining product integrity. The next phase will focus on upscaling these optimised conditions toward commercial application. Comprehensive flavour chemistry analysis, including volatile profiling and quantification of key aroma compounds, will be combined with modelling to define optimal curing conditions in commercial settings. Targeted screening of potential toxic compounds and nutritional analysis will ensure product safety and quality. The ultimate goal is to deliver a commercially viable vanilla extract that preserves flavour quality while substantially reducing curing time, labour demands, and production costs for the Australian vanilla industry.
Expected outcomes: Students will gain hands-on experience in a chemistry laboratory environment, including sample preparation, extraction, and analytical method application. They will develop practical skills in instrumental analysis using Gas Chromatography (GC) and High-Performance Liquid Chromatography (HPLC), as well as data interpretation. In addition, students will gain insight into food product development within an industry-focused research context, including considerations of flavour quality, safety screening, and commercial scalability.
Suitability: This project is suitable for 3rd–4th year undergraduate students or Master’s students with an interest in analytical chemistry and flavour chemistry. Applicants from agricultural science, food science, chemistry, or environmental science backgrounds are encouraged to apply. A basic understanding of laboratory practices and prior hands-on chemistry lab experience (e.g., sample preparation, solvent handling) is required.
Developing a food product with white Chlorella vulgaris processed with different methods
Primary Supervisors:
Prof Heather Smyth | h.smyth@uq.edu.au
Yifei Wu | yifei.wu@uq.edu.au
Please contact professeor Heather Smyth (h.smyth@uq.edu.au) and Yifei Wu (yifei.wu@uq.edu.au) before applying
Duration: 4 weeks (30 hours per week); onsite
Location: Long Pocket
Chlorella vulgaris is a sustainable protein source with a complete amino acid profile. However, the thick cell wall prevents intracellular nutrient release which impacts the functionality and nutritional value of Chlorella biomass. This project aims to understand the performance of ultrasound-treated Chlorella vulgaris in food products. The student will assess the performance of untreated and treated Chlorella in a formulated ice cream prototype in comparison to commercial soy protein and whey protein isolates. A descriptive sensory study will be conducted to assess appearance, odour, mouthfeel, flavour, afterfeel and aftertaste. Physical analysis such as microstructure, overrun and texture analysis of the ice cream will be performed and related to sensory properties.
Expected outcomes: The scholar will gain skills in protein extraction techniques, food product formulation, descriptive sensory analysis, and texture analysis and will collect research data that is expected to lead to a publication.
Suitability: This project is open to applicants with a background in food processing, food structure and food sensory, as well as statistical analysis.
Comparative Physicochemical and Functional Characterisation of Seven Oat Varieties
Primary Supervisors:
Dr Dilini Perera | d.perera@uq.edu.au
Dr. Gethmini Kodagoda | k.kodagoda@uq.edu.au
Contact Dr Dilini Perera(d.perera@uq.edu.au)or Dr. Gethmini Kodagoda (k.kodagoda@uq.edu.au) for any information about this project.
Duration: 4 weeks (30 hours per week); onsite
Location: Long Pocket
This study will investigate the proximate composition and functional properties of seven oat varieties through targeted laboratory analyses. Key compositional parameters will be determined alongside functional characteristics such as pasting behaviour and starch gelatinisation. The study aims to improve understanding of how varietal differences influence the functional performance of oats. The findings will provide practical insights into the suitability of different oat varieties for specific food applications.
Expected outcomes: The student will gain hands-on experience in understanding the properties of grains, flours, and food products derived from them, with a focus on functional, physical, and processing characteristics. The project will also develop skills in data analysis and basic statistical evaluation of experimental results, including interpretation of variability and comparison between oat varieties. Students will gain experience in translating analytical data into scientifically sound conclusions relevant to food science and product development.
Suitability: This project is suitable for 3rd–4th year undergraduate and master’s students with a background in food science.
Innovative New Product Development of a Variety of Beverage Products Leveraging Sensory and Analytical Methods for Guided Prototype Formulation
Primary Supervisors:
Mr Felix Briner | f.briner@uq.edu.au
Ms Theresia Konrad | t.konrad@uq.edu.au
Prof Heather Smyth | h.smyth@uq.edu.au
Please contact Mr Felix Briner (f.briner@uq.edu.au) if you have any questions.
Duration: 4 weeks (30 hours per week); onsite
Location: Long Pocket
With numerous challenges facing the global food industry, there is an increasing demand for sustainable, nutritious and affordable new food and beverage products that leverage new and existing ingredients. The new product development (NPD) team within CNAFS’s Sensory & Food Quality Team is working with industry partners to deliver innovative food & beverage products across numerous categories. This research project involves working with an experienced NPD beverage specialist Felix Briner to support development work on several projects, including an alcoholic distilled Cumquat spirit, brewed non-alcoholic soft drink, UHT milk drink, non-alcoholic cocktails with nootropic ingredients and more.
The selected participant will get hands on experience in NPD and work with Felix to prepare new prototype formulations, perform experiments, perform analytical and sensory testing, research and troubleshoot technical challenges, and draw on feedback and experiment results to plan subsequent product variants.
Expected outcomes:
Experience in NPD across several beverage product categories. Skills in researching and troubleshooting difficult and unforeseen challenges during product development. Experience preparing complex formulations using a variety of simple and advanced processing equipment in a laboratory setting. Experience conducting simple sensory experiments, and a variety of analytical measures.
Suitability: This project is suitable for Undergraduate or Masters students studying food science / technology or a related field with interest in NPD.
Metabolomics and Chemometrics to Discriminate the Geographical Origin of Lemon Myrtle
Primary Supervisor: Dr Maral Seididamyeh | s.maral@uq.edu.au
Please contact Dr Maral Seididamyeh (s.maral@uq.edu.au) if you have any questions.
Duration: 4 weeks (30 hours per week); On-site
Location: Long Pocket
This project focuses on the application of untargeted metabolomics to discriminate the geographical origin of lemon myrtle (Backhousia citriodora), an Australian native plant of high commercial value. The student will process LC–MS/MS datasets and apply chemometric and multivariate statistical analyses to compare metabolomic profiles of samples from different geographical locations.
Expected outcomes: Student will gain experience in metabolomics data processing, chemometric and multivariate statistical analysis for plant authentication studies. Deliverables include full chemometric analysis of the dataset to identify key discriminating metabolite features, a report and an internal presentation. If interested, the student will be encouraged to draft a research paper.
Suitability: 3rd or 4th year undergraduate or Master students with background in chemistry and an interest in food and biological sciences with skills in statistics and data analysis software (e.g. R, Python, or metabolomics platforms).