22 developer-"https:" "https:" "https:" "CNRS " PhD positions at Queensland University of Technology in Australia
Sort by
Refine Your Search
-
Training Program (RTP) Fee-Offset a four-year project expense and development package of $13,000 per annum a three-month industry engagement component with Gelomics a structured professional development and
-
proposed principal supervisor, and copy the link to this scholarship web page into question two of the financial details section. About the scholarship This project aims to develop advanced control
-
reconstruct the evolution of particle-laden turbulent flows from limited data using scientific machine learning. You will also be involved in the data-generation and curation for model development. Accordingly
-
the participating university, CSIRO, and an industry partner a four-year scholarship package totalling about $48,000 per annum tax exempt (2026 rate) a four-year project expense and development package starting from
-
, chemically demanding, and operationally complex. By developing porous structures that enable fluids to separate naturally through capillary and interfacial effects, this project aims to advance a more
-
focuses on developing the first-ever closed-loop cardiopulmonary resuscitation (CPR) feedback device. The device uses non-invasive sensors to measure blood oxygenation in the brain and tells the CPR
-
bridges and buildings by developing innovative, high performance protective columns. The proposed system features a composite column consisting of an outer Fibre Reinforced Polymer (FRP) tube, an inner
-
package totalling approximately $47,000 per annum tax exempt (2025 rate) a four-year Research Training Program (RTP) Fee-Offset a four-year project expense and development package of $13,000 per annum a
-
studies, sociology, anthropology, community development) or relevant undergraduate degree with honours demonstrated research capacity and critical thinking skills commitment to critical, feminist
-
, hyperspectral imaging provides an opportunity to develop fast and non-invasive methods of detecting plant diseases and potentially discriminating between different disease types (e.g. virus, fungus, bacteria