Intern projects

Supervisor: Dr Elise Kenny
Contact: e.kenny2@uq.edu.au

Description

Meltable metal-organic frameworks (MOFs) are good at absorbing light and can be easily modified and combined with other compounds. This means they are promising for artificial photosynthesis. Computer simulations of the melting properties of MOFs can help identify effective experimental techniques for their creation. Instead of using traditional methods that are slow and require a lot of computing power, we’ll use a faster, machine learning-based approach to model how atoms interact. This project will compare the results from this new method with older techniques to see how well it works.

Expected outcomes

The applicant will learn about modelling systems at the molecular level, and how applied fields and structural changes can affect melting properties. They will collect, analyse and visualise their data. At the end of the project the student will summarise their findings in a report and present the results to our group.

Candidate Attributes

This project is open to motivated students with a background in chemistry, physics or maths and an interest in computational science.

Supervisor: Dr Huadong Peng
Contact: huadong.peng@uq.edu.au

Description

This project will explore how engineered yeast cells can be programmed to communicate with each other using synthetic signalling pathways. By constructing genetic circuits that enable the production and detection of signalling molecules, students will study how communication networks can be built, tuned, and characterised in yeast. The project will combine molecular biology, synthetic biology, and microbiology techniques to design and test communication modules, with applications in synthetic microbial consortia and industrial biotechnology.

Expected outcomes

Skills and techniques learned:

• DNA assembly and molecular cloning (e.g. Golden Gate, Gibson, or CRISPR-based tools)
• Yeast transformation and culture techniques
• Reporter gene assays (e.g. fluorescence readouts) • Data analysis of gene expression and communication dynamics
• Literature review and scientific communication

Tasks:

• Construction of plasmids and engineered yeast strains
• Running growth and communication assays • Collecting and interpreting experimental data
• Documenting experimental progress in lab notes

Deliverables:

• A written report summarising methods, results, and interpretation
• An oral presentation at the end of the project

Candidate Attributes

• Students in Biotechnology, Molecular Biology, Biochemistry, Microbiology
• Suitable for 3rd year undergraduate students or master's student
• Interest in synthetic biology, metabolic engineering
• Willingness to undertake laboratory-based work and basic data analysis

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Supervisor: Dr Quang Loi
Contact: k.loi@uq.edu.au

Description

Nanobubble formation is essential for capture of minerals from solution. The effectiveness of capture depends on the complex nature of the mineral-water interface. Thus, the use of concentrated brines for the purpose of separation of KCl and NaCl minerals via the flotation process has been a research focus for many years, but there are still fundamental questions to answer. This project aims to use new machine learning potentials developed using artificial intelligence to understand the role of the electric double layers at high salt concentration and their effects on the mineral-water interfaces.

Expected outcomes

The student will gain experience in using computational software (mainly LAMMPS) in understanding the ion-specific effects at the molecular scale. In addition, the student will gain knowledge in the thermodynamics of aqueous solutions and the empirical equations commonly used in industry to model aqueous solutions. A short scientific report will be required towards the end of the project so that the student can gain a wholistic picture of the scientific experience.

Candidate Attributes

The project is open to chemistry or chemical engineering student who has a strong background in thermodynamics of phase transition and phase equilibria. An interest in computer science is also highly regarded.

Supervisor: Dr Vignesh Selvaprithiviraj
Contact: v.selvaprithiviraj@uq.edu.au

Description

Death from haemorrhage (bleeding) is preventable, yet it accounts for 30-40% of fatalities in civilian settings. In military environments, 90% of casualties with potentially survivable injuries succumb to uncontrolled bleeding. This project involves design and development of biomaterial-based delivery of snake venom active pharmaceutical ingredients for use as rapid wound sealants.

Expected outcomes

Skills and techniques learned:

• Mechanical properties such as rheology of hydrogels, In vitro blood clotting assays, confocal super resolution microscopy, chemical modification of biopolymers.

Deliverables:

• Compilation of data and findings as a report.

Candidate Attributes

Students in Biotechnology, Biomedical Engineering, Chemical Engineering Suitable for 3rd year undergraduate students or master students

Supervisor: Dr Huadong Peng
Contact: huadong.peng@uq.edu.au

Description

This project aims to engineer yeast Yarrowia lipolytica as an efficient cell factory to produce high-value lipids. Through metabolic engineering, pathway optimisation, the project will enhance precursor supply, redirect carbon flux, and overcome regulatory bottlenecks to achieve sustainable lipid production. Target lipids include omega-3 fatty acids for nutritional applications, and novel lipid-derived compounds with industrial and biomedical value. The project integrates synthetic biology tools with systems-level design to advance Y.lipolytica lipid engineering and provide sustainable alternatives to conventional lipid sources.

Expected outcomes

Skills and techniques learned:

• DNA assembly and molecular cloning (e.g. Golden Gate, Gibson, or CRISPR-based tools)
• Yeast transformation and culture techniques
• Lipid extraction and analysis
• Literature review and scientific communication

Tasks:

• Construction of plasmids and engineered yeast strains
• Collecting and interpreting experimental data
• Documenting experimental progress in lab notes

Deliverables:

• A written report summarising methods, results, and interpretation
• An oral presentation at the end of the project

Candidate Attributes

• Students in Biotechnology, Molecular Biology, Biochemistry, Microbiology
• Suitable for 3rd year undergraduate students or master student
• Interest in synthetic biology, metabolic engineering
• Willingness to undertake laboratory-based work and basic data analysis

Supervisor: Dr Yusra Rabbani
Contact: y.rabbani@uq.edu.au

Description

Gold nanoparticles have interesting optical properties. An example of this is their remarkable ability to convert light energy into heat. In this project you will be encapsulating biomolecules such as enzymes with polymer microcapsules that are embedded with gold nanoparticles. When these microcapsules are irradiated with specific wavelengths of light, this causes the capsules to rupture and release the biomolecule payload. For enzymes this allows time and site-specific release so that the biological enzymatic function can be controlled both spatially and temporally at will.

Expected outcomes

Synthesis or assembly of microparticles, synthesis of gold nanoparticles, assessing enzyme release, and particle characterisation

Candidate Attributes

 Students studying chemistry or biotechnology

Supervisor: Dr Luke Wylie
Contact: l.wylie@uq.edu.au

Description

The ability of carbon dioxide to actively move through an electrolyte is of prime importance when considering an electrolyte to use in a CO2 reducing cell setup. In this project the student will use molecular dynamics (MD) simulations to quantify the diffusion of CO2 in the presence of different cations possible in electrolytes and determine the impact of cations in reducing or enhancing the ability of CO2 to diffuse

Expected outcomes

The student will ideally calculate the diffusion coefficients for CO2 in a variety of aqueous electrolytes. These will be obtained from analysis from conducted simulations and can be used for experimental applications.

Candidate Attributes

Chemistry or computer science students with an interest in chemistry. Ideally students will have a background in using Python to code or use of a Linux terminal.

Supervisor: Prof Mehdi Mobli

Contact: m.mobli@uq.edu.au

Description

Optimise and produce cyclic variants of ApoA-I using our autocyclase platform. This procedures involves bacterial protein expression, IMAC, HPLC an FPLC purification. Characterisation of the products will be performed using a variety of analytical methods including, MS, NMR and DLS.

Expected outcomes

You will learn the basics of protein biochemistry including basic analytical skills. You will be expected to produce highly pure products for downstream testing in nanoparticle formulations for mRNA vaccine delivery.

Candidate Attributes

Students with a suitable background in chemistry or biochemistry are encouraged to apply.

Supervisor: Dr Axayacatl Gonzalez
Contact: r.gonzalezgarcia@uq.edu.au

Description

IDEA bio has been established as a fermentation biofoundry for the characterisation of bioprocesses. This project is targeted for students eager to learn about the use of bioreactors and the analysis of microbial fermentation implementing a systems biology and multimers approach. At IDEA bio, we have developed microbial cell factories that will be tested in parallel bioreactor so we can develop novel strategies for the development of bioprocesses. This internship is ideal for students interested in hand on experience in bioprocesses and for students interested in the analysis of multiomics data using novel approaches including AI and machine learning.

Expected outcomes

Students will be onboarded in IDEA bio and will learn the basic elements for the cultivation of microorganism and the operation of bioreactors. Depending on the interests of the students, the project can be wet lab or dry lab focused. As members of IDEA bio, students will be mentored by fermentation scientist, systems biologist and other specialists in the development of bioprocesses and the analysis of data. By the end of the internship, it will be expected for students to present their learnings and results in a seminar.

Candidate Attributes

2 positions available. Background on science, chemical engineering, computational modelling. Interested in learning about systems and synthetic biology in a biofoundry context. Experience in basic lab task is desired, but not necessary.

Supervisor: Dr Nicholas Fletcher
Contact: n.fletcher1@uq.edu.au or k.thurecht@uq.edu.au

Description

Nanomedicine, the application of nanotechnology and biotechnology to medicine, is a rapidly expanding field of research with great promise for making meaningful changes in the way we treat many diseases including cancer. Targeted nanomedicines capable of selectively delivering radiotherapies to tumours in a precision medicine approach are particularly appealing as these enhance tumour treatment while limiting unwanted off-target effects. We have recently developed a variety of targeting approaches, where we are able to decorate the surface of either nanomaterials or tumours with ligands able to enhance nanomaterial tumour accumulation (Figure). This project will work to further develop these targeting strategies, including evaluating materials with altered pharmacokinetics, ligands for novel cancer types, and improve our understanding of bionano interactions by studying the cellular interactions of nanomaterials within the tumour and clearance organs in the body. PET-CT image demonstrating enhanced tumour localization of pre-targeted nanomedicine (bottom panel) compared to conventional targeting approach (top). Arrowheads highlight tumours.

Expected outcomes

This project will allow students to gain skills in a variety of synthetic and analytical techniques, primarily in monitoring nanomedicine/protein association and cellular interactions using equipment based at the Australian Institute for Bioengineering and Nanotechnology (AIBN). During the course of the project they will also be provided exposure to a range of advanced imaging modalities (Optical imaging, SPECT, PET-CT and PET-MR imaging) at the Centre for Advanced Imaging (CAI). Being based within the Thurecht Group they will also be able to gain a broad experience and understanding of nanomedicine science, with the opportunity to be involved in multiple projects. The results from this work will be written up by the student at the end of the project and potentially form this basis of publications.

Candidate Attributes

This project utilizes a multidisciplinary approach and will be suitable for all students with an interest in nanomedicines and biology/biophysical chemistry. However given the technical nature of the work involved 2-3 rd year biomedical/biology (or equivalent relevant experience) background will be better suited to achieve the most from the project

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Supervisor: A/Prof Brett Paterson
Contact: brett.paterson@uq.edu.au
Applicants should contact Brett prior to submitting an application.

Description

Metals play many important roles in medicine as metal-based materials, metallodrugs and agents for detecting and treating diseases. The biological applications can be influenced by the general properties and structure of the molecules or materials. We are a synthetic chemistry and radiochemistry group developing targeted radioactive agents called radiopharmaceuticals, for imaging and treating diseases such as cancer. This project will involve synthetic chemistry and radiochemistry and the use of analytical techniques such as iTLC and HPLC to characterise new molecules.

Expected outcomes

The student will gain experience in synthesis and analytical chemistry techniques, where they will be synthesising and characterising newly designed molecules. The student will have the opportunity to learn radiochemistry techniques in a state-of-the-art radiochemistry facility using radionuclides. Students will be shown how to keep experimental notes and how to write a scientific report that may become part of a publication. Students will be given opportunities to produce an oral presentation to colleagues and engage in scientific discussions across a broad range of research areas.

Candidate Attributes

This project will be suitable for students with an interest in chemistry and radiochemistry. This project is open to 2nd – 4th year students with a background and interest in organic/inorganic chemistry.

Supervisor: Dr Birgitta Ebert

Contact: birgitta.ebert@uq.edu.au or h.ehlert@uq.edu.au

Description

Project goal and context. Optimising media for the microbial production of high-value chemicals is an important but complicated endeavour. Defined growth media often contain ≥10 interacting components (salts, trace minerals, vitamins), each influencing microbial growth and yield. Because changing one concentration can shift requirements for others, brute-force screening is infeasible. Bayesian optimisation (BO) strategically explores this combinatorial space, proposing the most informative experiments to maximise product formation with minimal lab work. We aim to identify a cost-effective medium that maximises squalene and squalene-derivative production in Saccharomyces cerevisiae, a well-established triterpenoid host with native squalene biosynthesis. Approach. (i) Literature review to shortlist key medium factors; (ii) high-throughput screening using liquid-handling robots and Growth Profilers (up to 960 parallel cultures); (iii) BO modelling (in collaboration with computational experts) to select the next experiment batch; (iv) iteration until an optimum is reached.

Expected outcomes

Skills & techniques learned

• High-throughput cultivation design and execution; plate layout/randomisation; sterile technique at scale.
• Lab automation (liquid handling), Growth Profiler operation, and assay QC (controls, replicates, variance estimation).
• Data management and analysis: preprocessing, outlier handling, uncertainty quantification, and sensitivity/robustness analysis.
• Bayesian optimisation fundamentals (surrogate models, acquisition functions) and comparison to classical DoE.
• Optional analytics exposure for squalene quantification (e.g., GC-FID/GC-MS or LC-MS sample prep and basic method use).

Computational competencies

• Implementing BO workflows in Python/R (notebooks, reproducible pipelines), basic visualisation (response surfaces, EI maps), and cost-aware objective functions.

Core tasks

• Curate literature on media components for squalene overproduction; define factor ranges.
• Plan and run microscale screens; maintain accurate metadata; ensure experiment integrity and throughput.
• Fit/update BO models; interpret model uncertainty; propose next-round conditions; document decisions.
• Validate top media in confirmatory runs; benchmark against a baseline medium; assess transferability to bioreactor-like conditions.

Deliverables

• An optimised, cost-aware medium formulation with documented tolerance windows.
• A reusable analysis pipeline (code + brief user guide) for BO-driven media optimisation.

Assessment outputs: written report and oral presentation to the group.

Candidate Attributes

• Background in microbiology/biotechnology with strong experimental rigour and attention to QC.
• Quantitative mindset; readiness to learn BO and uncertainty-aware decision-making (prior coding/statistics helpful but not essential).
• Reliability with lab automation, careful data curation, and clear scientific communication (concise writing and presentation).

Supervisor: Dr Hao Song

Contact: h.song6@uq.edu.au

Description

Dive into the cutting-edge science behind modern vaccines! This hands-on project involves creating the next generation of mRNA lipid nanoparticles (LNPs)—the same technology used in COVID-19 vaccines. You'll learn to formulate these tiny ""nano-capsules"" and then investigate the thrilling part: how they interact with immune cells. We'll unlock how their design triggers a powerful immune response, aiming to design super-efficient vaccines from the ground up. This is your chance to directly contribute to the future of medicine and see immunology and nanotechnology in action.

Expected outcomes

• Skills: Hands-on training in mRNA-LNP formulation (microfluidics), nanoparticle characterization (DLS/NTA), cell culture, and ELISA cytokine analysis.
• Tasks: Synthesize and characterize LNPs, apply them to immune cells, and quantify cytokine output to link LNP properties to immune activation.
• Deliverables: A concise final report (5-7 pages) and a 10-minute oral presentation to the research group.

Candidate Attributes

• Students in Biotechnology, Molecular Biology, Immunology
• Suitable for 3rd year undergraduate students or master student (not in their final semester of study in RQ1 2026)
• Interest in nanotechnology and vaccine development

Supervisor: Dr Will Anderson
Contact: w.anderson1@uq.edu.au

Description

This research project will focus on developing methodology for the microscopy of single fluorescent molecules.

Expected outcomes

The project will teach skills in ELISA-like protein quantification, fluorescent microscopy, and automated image characterisation software. A short oral presentation on the research performed will be required at the end of the project.

Candidate Attributes

The project will be suitable for first/second year molecular biology and biotechnology students interested in diagnostics assay development or diagnostic device design.