We're looking for multiple students to help us answer the question: 'How can we utilise information technology to aid ecological research?'
Sensor networks bring ecologists and pattern recognition researchers together to make some applications possible. These applications include assessing risks from potential bird collisions, unobtrusive observations (where the presence of humans changes some animal behaviours) and studying spatial and temporal variation in biological processes.
With a significant amount of data being collected from these applications, processing and mining this data is challenging. One approach is to apply existing high performance computing, data management and analysis solutions to specific scientific challenges and solve any new problems that arise.
We'll conduct a systematic investigation on effective data analysis and pattern recognition methods. This project is in partnership with the QUT Ecoacoustic research group, one of the world's leading groups in this area.
This project will investigate algorithms that recognise animal species using machine learning and image processing techniques. We'll also investigate semi-automated analysis and citizen science approaches.
You'll have the opportunity to work on a specific aspect of the project. This can include:
- computer-human interaction
- information retrieval
- machine learning
- signal processing
- pattern recognition.
The project's scope and activities will vary based on your level of study. You can expect to:
- conduct a literature review
- frame specific research questions
- design solutions addressing the research questions
- conduct experiment to evaluate your solutions
- analyse and document your results
- disseminate your findings in the form of reports, papers and oral presentations.
The outcomes of this project include:
- novel algorithms
- software prototypes
- reports and/or research papers.
If you're undertaking a VRES project, you're only expected to join our existing research team and modify or evaluate some of our existing algorithms or techniques.
Skills and experience
As the ideal candidate you should have background in any of the following disciplines:
- computer science
- information systems
- data science
- engineering majoring in computer and software systems.
You should also have knowledge and skills in computer programming or data analysis.
You may be able to apply for a research scholarship in our annual scholarship round.
Contact the supervisor for more information.