37 phd-position-for-fully-funded-reserch-in-computer-vision Fellowship positions at Monash University
Sort by
Refine Your Search
-
Iadine Chades, Director Environmental Informatics Hub, iadine.chades@monash.edu or +61 418 684 902 Position Description: Research Fellow Applications Close: Monday 6 October 2025, 11:55pm AEDT Supporting
-
algorithms and techniques and design, implement, test, and maintain software/tools embodying those methods. You will prepare and submit grant proposals to external funding bodies. This position will also
-
computation in science and engineering; Advanced materials and manufacturing; Energy and environment; Future cities; and Life sciences We are seeking an individual passionate about undertaking research in
-
. We are currently seeking a Research Fellow with experience in AI and machine learning research and development, with a focus on any or all of following application areas: Computer vision Generative AI
-
Centre for Advanced Photovoltaics, collaborating with leading researchers and contributing to high-impact publications, patents, and funding proposals. Your work will directly support the development
-
projects within the Korean Studies discipline. This position supports the strategic goals of the Monash University Korean Studies Research Hub by actively engaging in scholarly inquiry and enhancing
-
Group’s research programme for the development of therapeutic biomolecules. You will work as part of a team using cutting edge synthetic techniques to develop safer drug targeting systems based
-
for drug discovery. Publishing peer-reviewed research and contributing to industrial software tools. About You To be successful in this role, you will have: A PhD in machine learning, computer
-
fast-readout electron detectors to validate the methods developed. The successful candidate will have a PhD in Physics, Materials Engineering, Computer Science or a closely related field. Research
-
an interdisciplinary, purpose-driven team. You have: A postgraduate qualification in Computer Science, Data Science or related field Extensive experience working with large-scale, high-frequency (waveform) data