GenAI Models for Source Code Generation

About the research project

Generative AI is a subfield of AI that uses generative models to produce text, images, videos, and program source code. These models can learn the underlying patterns and structures of their training data and use them to produce new data based on an input, which usually comes in the form of natural language prompts. Among Generative AI models, Large Language Models (LLMs) have demonstrated significant potential in the realm of natural language processing and programming source code generation. LLMs can generate program source code based on problems or instructions written in natural language. They can also describe code in natural language or translate between programming languages. Code generation denotes software techniques or systems that generate program source code which may then be used independently of the generator system in a runtime environment. Code generation is important because it automates the process of creating code, saving time, reducing errors, and promoting consistency across projects. It allows developers to focus on higher-level tasks and innovation rather than repetitive coding tasks. Currently, LLMs for code generation are rapidly evolving, however, there are significant challenges which need to be tackled. Such challenging tasks include: 1) Many LLMs demonstrate strong general performance but have not been thoroughly evaluated on code generation benchmarks; 2) Most LLMs continue to struggle with code correctness, particularly on complex tasks; 3) Limitations of current optimisation methods for achieving higher code correctness; and 4) Ongoing issues such as hallucination and data contamination. This project intends to conduct a comprehensive evaluation of the currently popular LLMs and optimisation techniques on code generation tasks and develop a more effective model (or a combination of models) to assist automatic coding.

Primary supervisor

Meet Doctor Shuxiang Xu

Funding

Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

• a living allowance stipend funded by University of Tasmania of $34,315 per annum for 3.5 years
• a relocation allowance of up to $2,000
• a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

A tuition fee offset may be offered to eligible international applicants following competitive assessment 

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.

Other funding opportunities and fees

For further information regarding other scholarships on offer, and the various fees for undertaking a research degree, please visit our Scholarships and fees on research degrees page.

Eligibility

Applicants should review the Higher Degree by Research minimum entry requirements.

Ensure your eligibility for the scholarship round by referring to our Key Dates.

Additional eligibility criteria specific to this project/scholarship:

• Applications are open to Domestic/ International/ Onshore applicants

Selection criteria

The project is competitively assessed and awarded. Selection is based on academic merit and suitability to the project as determined by the College.

Additional essential selection criteria specific to this project:

Masters by Research in the domain of ICT

Or

Masters by course work with a research component in the domain of ICT

Or

Bachelors (Hons) of at least second class upper with a research component in the domain of ICT

Additional desirable selection criteria specific to this project:

• Programming experience in a high level programming language such as Python or C or Java; Deep Learning experience

Application process

1. Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
2. Contact Doctor Shuxiang Xu to discuss your suitability and the project's requirements; and
3. In your application:
   • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
   • Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
4. Apply prior to 1 October 2026.

Full details of the application process can be found under the ' How to apply ' section of the Research Degrees website.

Following the closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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