Sort by
Refine Your Search
-
Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning
-
This PhD research scholarship (Learning Lessons from Drug Resistance to Tackle Herbicide Resistance) is funded by the Australian Research Council to support a full-time PhD student to undertake
-
The Australian Institute for Machine Learning (AIML) offers new PhD scholarship opportunities in Industrial AI. These full-time scholarships support students undertaking their PhDs in AI and machine
-
excellence by providing a highly collaborative environment that benefits the research of all its scientists, whether at the graduate, post-doctoral or group leader level. A key initiative of the associate
-
into fundamental molecular events. At the same time, access to translational pipelines will enable the candidate to apply their learnings in a meaningful way, revealing novel therapeutic targets critical for cancer
-
educational powerhouse that fosters economic and social wellbeing through ground-breaking research and innovative teaching. You can learn more about Adelaide University HERE and more information will be
-
). No extensions shall be considered. Eligibility To be eligible for the Scholarships, applicants must be: Commencing a full-time Doctor of Philosophy program in engineering at the University of Adelaide
-
where? Eligibility: Applicants must be accepted for admission into a Doctor of Philosophy at the University of Adelaide and enrolling in one of the 5 approved PhD projects . Applicants must be awarded a
-
research in the field of sustainable housing. Assisting the organisation in developing a cutting-edge, AI-driven platform for home retrofitting digital products. Learning about the integration of AI with
-
; Enrolled in a Doctor of Philosophy (PhD) program at the University of Adelaide; A recipient of a major scholarship; and Undertaking research relevant to environmental sustainability. *Note, environmental