Research Fellow

at  Griffith University

EVERY INSTITUTION VALUES EXCELLENCE. WHAT MATTERS MOST IS WHY.

Griffith was created to be a different type of university. You’ll find we’re about leading research, academic excellence, and the transformative power of education. But what sets us apart is why those things matter and how you’ll achieve them.
Why? Griffith brings together exceptional minds like yours from across the globe and from all walks of life. Here, we do incredible work, questioning and challenging, always in the pursuit of excellence.
Job Description
The Institute for Integrated and Intelligent Systems (IIIS) was established in 2003 to enhance Griffith’s ICT research environment and stimulate world class research. Our Computer Science and Engineering discipline at Griffith University (Research Output) is currently ranked, by Academic Ranking of World Universities among the top 76-100 in the world, a testimony to the high quality and global recognition of our research.
Griffith University’s ARC Research Hub are seeking an enthusiastic researcher in deep learning, machine learning, and computer vision. The ARC Research Hub for driving farming productivity and disease prevention is an Australian research centre of excellence for industrial transformation funded by Federal Government and industry. This Griffith University led ARC Research Hub consists of 5 universities and 5 industrial partners. The mission for this ARC Research Hub is to significantly increase farm production and disease prevention ability through advancing and transferring new artificial intelligence technologies into industrial deployment.

KEY REQUIREMENTS OF THIS POSITION INCLUDE:

• Conduct research aligned with the goals of the Centre/Institute to advance knowledge and achieve research objectives.
• Develop a strong publication record by publishing research findings in reputable international journals and conferences. Additionally, actively seek competitive funding opportunities for research projects.
• Specialise in fine-grain visual classification in agriculture, encompassing fundamental theories, new approaches, algorithms, technical investigations, system implementations, and experiments for research projects.
• Collaborate with team members on research projects, contributing to their development and preparation. Foster a collaborative research environment.
• Engage in teaching activities as required and provide mentorship and supervision to research higher degree students. Help nurture the next generation of researchers.
  This is a fixed term (2 years), full time position and will be primarily based at the Griffith University Nathan campus. As Griffith is a multi-campus University you may be required to work across other campus locations.
  The successful candidate will be appointed at either Grade 1 or 2 depending on experience, skills and qualifications.
  Griffith University’s campuses are located on the lands of the Yugarabul, Yuggera, Jagera, Turrbal, Yugambeh and Kombumerri peoples.

SALARY RANGE

The full time equivalent base salary for Research Fellow (Grade 1) range $84,830 - $99,367per annum + 17% superannuation. The total FTE package will be in the range $99,251- $116,259 per annum.
The full time equivalent base salary for Research Fellow (Grade 2) range $108,298 - $128,608 per annum + 17% superannuation. The total FTE package will be in the range $126,709- $150,471 per annum.
Qualifications
The ideal candidate for this position should possess a PhD in computer science, engineering, applied mathematics, or a related field, along with a keen interest in advancing their career in machine learning, deep learning, artificial intelligence, and computer vision.
The occupant of this position must have a proven track record in conducting research, including publications in esteemed journals and conferences such as IEEE TPAMI, IEEE TIP, PR, CVPR, ICCV, IJCAI, AAAI. We are looking for an enthusiastic individual dedicated to becoming a valuable member of our research team.
Additional Information

Please refer the Job description for details