Centre for Animal Science - Summer Research Programs

Primary Supervisor: A/Prof Elizabeth Ross | e.ross@uq.edu.au

To express interest, please send a brief CV and summary of your relevant skills and experience to Associate Professor Elizabeth Ross and Dr Loan Nguyen.

Duration: 6 weeks (36 hours per week); On-site (St Lucia Campus). 

We are seeking a motivated Master of Bioinformatics student to develop a reproducible Nextflow pipeline for a USDA–NIFA-funded project investigating gene regulation and enhancer activity in Bos taurus and Bos indicus cattle.

The student will design, test and document a workflow for processing large-scale functional genomics data, incorporating quality control, standardised analysis steps and reproducible reporting. The pipeline will support an international collaboration involving UQ, Texas A&M University and the USDA.

This project would suit a student with experience in Linux, scripting and genomic data analysis. Familiarity with Nextflow, containers or high-performance computing is desirable but not essential. The project offers hands-on experience in workflow development, cattle genomics and collaborative research, with the potential to contribute to research outputs.

Key activities student will undertake: 

• Review the project’s analysis requirements and relevant genomic datasets.
• Design and build a modular, reproducible Nextflow pipeline.
• Implement sequence-data quality control, processing, analysis and reporting steps.
• Use containers and version control to ensure the workflow is portable and reproducible.
• Test and optimise the pipeline using project data and UQ high-performance computing resources.
• Produce clear technical documentation and user instructions.
• Present the completed workflow and results to the research team and international collaborators.

Expected outcomes: 

Students will gain practical experience in Nextflow workflow development, genomic data analysis, Linux, high-performance computing, version control, containerisation and reproducible research. They will also develop skills in troubleshooting, technical documentation, communicating results and working within an international research collaboration.

By the end of the project, the student is expected to deliver a tested, modular and documented Nextflow pipeline for processing the project’s functional genomics data. Additional outputs will include version-controlled code, automated quality-control and summary reports, user documentation, and a presentation of the workflow and initial results to the research team.

Suitability: This project is suitable for a Master of Bioinformatics student with an interest in genomics, workflow development and reproducible research. Applicants should have some experience with Linux and at least one scripting language, such as Python, R or Bash. Coursework or experience in genomics, sequence-data analysis, high-performance computing, Git, containers or Nextflow would be beneficial but is not essential.

The ideal student will be curious, organised and willing to develop a deep understanding of the analytical workflow. They should enjoy problem-solving and troubleshooting, be able to work independently while seeking guidance when needed, and communicate and document their work clearly.

Primary Supervisors: 

Dr Karishma Mody | k.mody@uq.edu.au 
Miss Yakun Yan | yakun.yan@uq.edu.au

Please contact Dr Karishma Mody (k.mody@uq.edu.au) before submitting an application.

Duration: 6 weeks (30 hours per week); On site (St Lucia Campus)

RNAi-based control of sheep flystrike has the potential to provide a species-specific and environmentally sustainable alternative to chemical insecticides. However, successful application is hindered by dsRNA degradation and inefficient delivery to target tissues in blowfly larvae. This project will evaluate dsRNA and BenPol-based delivery formulations to improve RNA stability, uptake, and gene silencing efficacy, while establishing a robust experimental platform for the development of next-generation RNA biopesticides.

Key activities student will undertake: Prepare and characterise dsRNA formulations, including structured RNA and delivery-enhancing compounds. Perform/assist with laboratory experiments to evaluate dsRNA stability and persistence under simulated environmental conditions. Perform bioassays with blowfly larvae to assess dsRNA uptake and gene-silencing efficacy. Analyse experimental data using statistical and graphical methods. Participate in regular project meetings, present findings, and contribute to scientific reporting.

Expected outcomes: Students will gain hands-on experience in molecular biology, insect bioassays, experimental design, and data analysis within the context of developing sustainable livestock pest-control technologies. They will develop skills in RNA handling, laboratory safety, scientific communication, critical analysis of research literature, and interpretation of experimental results. The project will also provide insight into translational research aimed at improving animal health and welfare.

Suitability: Student's with an interest in molecular biology, entomology, animal welfare or a related discipline. Basic laboratory experience in molecular biology would be advantageous.

Primary Supervisor: Dr Stephen Ogada | s.ogada@uq.edu.au

Please contact Dr Stephen Ogada (s.ogada@uq.edu.au) before submitting an application.

Duration: 6 weeks (30 hours per week); On-site (Gatton Campus). 

Geographic isolation, insect vector dynamics, and other factors seem to strongly influence the molecular evolution of livestock viruses in Australia, differently from other parts of the world. This project aims to examine these differences and the forces behind them.

Key activities student will undertake:

1. Data retrieval of viral genome data.
2. Molecular analysis of data using bioinformatics tools
3. Results interpretation.

Expected outcomes: The student will gain hands-on bioinformatics analysis skills. 

Suitability: Students with an interest in animal science and bioinformatics. No prior coding experience required. Be willing to learn. 

Primary Supervisor: Dr Stephen Ogada | s.ogada@uq.edu.au

Please contact Dr Stephen Ogada (s.ogada@uq.edu.au) before submitting an application.

Duration: 6 weeks (30 hours per week); On-site (Gatton Campus). 

Point-of-care testing (POCT) offers rapid, accessible diagnostic solutions that facilitate timely detection and management of infectious diseases, particularly in resource-limited and field settings. This project aims to develop a rapid and field-deployable point-of-care diagnostic test for pestiviruses using isothermal amplification technology.

Key activities student will undertake:

1. Nucleic acid extraction or synthesis.
2. PCR and Isothermal amplification
3. Results interpretation.

Expected outcomes: The student will gain hands-on molecular biology skills.

Suitability: Students with an interest in animal science and molecular biology.

Primary Supervisor: Dr Stephen Ogada | s.ogada@uq.edu.au

Please contact Dr Stephen Ogada (s.ogada@uq.edu.au) before submitting an application.

Duration: 6 weeks (30 hours per week); On-site (Gatton Campus). 

This project aims to develop a long-read sequencing protocol to identify pathogens in test samples delivered to UQ Gatton.

Key activities student will undertake:

1. Nucleic acid extraction.
2. Sequencing
3. Molecular analysis of data using bioinformatics tools
4. Results interpretation.

Expected outcomes: The student will gain hands-on molecular biology and bioinformatics analysis skills.

Suitability: Students with an interest in animal science and molecular biology.

Primary Supervisor: Dr Loan Nguyen | t.nguyen3@uq.edu.au

Please contact Dr Loan Nguyen (t.nguyen3@uq.edu.au) before submitting an application.

Duration: 6 weeks (30 hours per week); On-site (St Lucia Campus). 

Puberty is a critical developmental stage that influences reproductive performance and lifetime productivity in cattle. However, the molecular changes associated with the transition from pre-pubertal to post-pubertal stages are not yet fully understood.

This project will use Oxford Nanopore Technologies long-read sequencing to investigate genomic and epigenomic variation in pre- and post-pubertal heifers. Students will gain hands-on experience in preparing high-molecular-weight DNA, assessing DNA quantity and quality, preparing sequencing libraries, and operating Oxford Nanopore sequencing platforms.

Depending on project progress and student interests, sequencing data may also be used to examine DNA methylation patterns, structural variation, and other genomic features associated with puberty. The project provides an opportunity to work across both wet-lab molecular biology and modern genomic technologies, contributing to a broader research program aimed at improving our understanding of reproductive development in cattle.

Key activities student will undertake: 

• Students will participate in some or all of the following activities:
• Preparation and quality assessment of DNA from pre- and post-pubertal heifer samples.
• Measurement of DNA concentration and purity using standard laboratory equipment such as Qubit and NanoDrop.
• Preparation of Oxford Nanopore sequencing libraries.
• Operation and monitoring of Oxford Nanopore sequencing runs.
• Assessment of sequencing performance, including read yield, read length and sequencing quality.
• Basic processing and quality control of long-read sequencing data.
• Comparison of sequencing results between pre- and post-pubertal animals.
• Depending on progress, preliminary analysis of DNA methylation and/or structural genomic variation.
• Documentation, interpretation and presentation of experimental results.

Expected outcomes: By participating in this project, students will develop practical experience in molecular biology, long-read sequencing and genomic research. They will gain an understanding of the complete sequencing workflow, from biological sample and DNA preparation through to sequencing, quality control and interpretation of genomic data.

Students will develop skills in:

• High-molecular-weight DNA preparation and quality assessment.
• Oxford Nanopore library preparation and sequencing.
• Experimental planning, sample tracking and laboratory record keeping.
• Sequencing quality control and interpretation of sequencing metrics.
• Basic bioinformatics and genomic data analysis.
• Critical evaluation and interpretation of experimental results.

Suitability: This project would suit students from disciplines such as biotechnology, molecular biology, genetics, genomics, animal science, biomedical science or related areas. Previous experience with molecular biology techniques is helpful but not essential, as training will be provided. Students with experience in DNA extraction, pipetting, PCR, sequencing, bioinformatics or basic data analysis would be particularly well suited.

Primary Supervisor: Dr Loan Nguyen | t.nguyen3@uq.edu.au

Please contact Dr Loan Nguyen (t.nguyen3@uq.edu.au) before submitting an application.

Duration: 6 weeks (36 hours per week); On-site (St Lucia Campus). 

DNA methylation can be measured using several sequencing and array-based technologies, each differing in genomic coverage, resolution, accuracy, cost and analytical requirements. This project will systematically compare methylation technologies using matched or comparable datasets to determine how technology choice influences methylation detection and biological interpretation. The findings will help guide the selection of appropriate technologies for future genomics research.

Key activities student will undertake: 

• Review the major technologies available for measuring DNA methylation.
• Develop a systematic framework and evaluation criteria for comparing technologies.
• Process and quality-check methylation datasets using established bioinformatics workflows.
• Compare genome coverage, sequencing depth, CpG detection, reproducibility and agreement between technologies.
• Investigate whether technology-specific differences affect the identification of differentially methylated regions or other biological conclusions.
• Produce statistical summaries and visualisations of the results.
• Document the analysis and present recommendations to the research team.

Expected outcomes: Students will gain practical experience in methylation analysis, genomic data processing, statistical comparison and reproducible bioinformatics. They will develop skills in Linux, R or Python, quality control, data visualisation, interpretation of complex genomic datasets and scientific communication.

Expected outputs include a reproducible analysis workflow, a documented comparison of the evaluated technologies, publication-quality tables and figures, and an evidence-based recommendation outlining the strengths, limitations and most appropriate applications of each technology. The student will also present their findings to the research team.

Suitability: This project is suitable for a Master of Bioinformatics student with an interest in genomics, epigenetics and sequencing technologies. Applicants should have some experience with genomic data analysis and at least one scripting or statistical language, such as R or Python. Familiarity with Linux, sequence-data processing, statistics or DNA methylation would be beneficial but is not essential.

The ideal student will be curious, analytical and attentive to detail. They should enjoy investigating why analytical methods produce different results, be willing to troubleshoot technical problems, and be able to work independently while clearly documenting and communicating their work.

Primary Supervisor: Dr Christie Warburton | c.warburton@uq.edu.au

Please contact  Dr Christie Warburton (c.warburton@uq.edu.au) before submitting an application.

Duration: 6 weeks (20 hours per week); On-site (Gatton Campus). 

Heat stress is a major challenge for dairy production in tropical environments. This project will investigate the genetic basis of thermotolerance in Indian smallholder dairy buffalo by performing a genome-wide association study (GWAS) for panting score, a measure of heat stress response. The aim is to identify genomic regions associated with heat tolerance that could support future breeding programs.

Key activities student will undertake: 

1. Use R for data exploration, visualisation, and statistical analyses.
2. Run GWAS analyses using GCTA on a high-performance computing (HPC) platform.
3. Interpret and visualise GWAS results.

Expected outcomes: The student will develop practical skills in genomic data analysis, R programming, data visualisation, and genome-wide association studies, while gaining experience using Linux/Bash and high-performance computing environments to analyse large livestock genomic datasets and communicate research outcomes

Suitability: Suitable for students with an interest in genetics, animal science, bioinformatics, or data science who are keen to develop skills in genomic analysis, programming, and quantitative research.