Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
PRIMARY DETAIL - Salary Package: $109,272 – $117,108 per annum ((Level A.6–A.8, PhD Awarded Rate), plus 17% employer's superannuation and annual leave loading. - Appointment Type: Full-time, fixed
-
Mechanical and Mechatronic Engineering (AMME) is one of Australia’s leading research and teaching Engineering Schools, with degree programs in Mechanical, Mechatronic, Aeronautical and Space Engineering. The
-
) A PhD in a related discipline, and/or relevant work experience. Experience in at least two of the following areas: engineering design, thermodynamics calculations, heat transfer, fluid flow, radiation
-
in physics, photonics, electrical engineering, or a closely related discipline demonstrated experience conducting original research in photonics or a related field expertise or strong research interest
-
demonstrated experience conducting original research in photonics or a related field expertise or strong research interest in nonlinear optics, integrated photonics, or RF photonics a developing research profile
-
across multiple ARC and other funded projects. This role reports to Professor Rukmi Dutta and works closely with the broader supervisory team. No direct reports. Level A, Salary – AUD $113,911 to $121,838
-
Full-time, 12-month fixed-term opportunity, with possibility for extension Exciting opportunity for a Postdoctoral Research Associate (Level A) to join the Matilda Centre for Research in Mental
-
research at the intersection of engineering, systems thinking, and organisational studies. We are seeking a Postdoctoral Research Associate (Level A) to join a new research stream focused on digital twins as
-
opportunity for a Postdoctoral Research Associate (Level A) to join the Matilda Centre for Research in Mental Health and Substance Use on an MRFF-funded trial of an online intervention to improve mental health
-
organisational studies. We are seeking a Postdoctoral Research Associate (Level A) to join a new research stream focused on digital twins as adaptive decision infrastructure for complex cyberphysical human systems