Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Monash University
- Curtin University
- RMIT University
- The University of Queensland
- University of Adelaide
- Nature Careers
- Queensland University of Technology
- University of New South Wales
- CSIRO
- Flinders University
- RMIT UNIVERSITY
- University of Southern Queensland
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- Australian National University
- Central Queensland University
- University of Technology Sydney
- 6 more »
- « less
-
Field
-
campus, but may be required to travel to other University campuses In the School of Computing Technologies, we aim to change student experience by embracing evidence-informed pedagogical strategies, and
-
at the City campus, but may be required to travel to other University campuses In the School of Computing Technologies, we aim to change student experience by embracing evidence-informed pedagogical strategies
-
AI/ML for Object Tracking and Sensor Fusion, you will develop next-generation algorithms that power intelligent aerial systems—enabling real-time object tracking, multi-sensor data fusion, and
-
publicly available datasets; 3) Proposing algorithms aimed at improving the accuracy of human activity detection; 4) Implementing these algorithms, evaluating their performance empirically, and comparing
-
-disciplinary Engineering Services Team within the College of Science & Engineering, where the Computer Systems Engineer supports the College of Science and Engineering by delivering high-quality technical
-
the headspace website. Possible approaches to addressing this challenge might include: Developing algorithms to identify patterns and preferences based on service users’ previous content engagement
-
programming and data analysis. Interest in developing methods, algorithms or software. Evidence of publications in high-quality peer-reviewed journals. Excellent communication skills. Experience
-
applied physics other related disciplines. Demonstrated knowledge in at least one of the following areas: porous media flow computational fluid dynamics (CFD) pore-network modelling lattice Boltzmann method
-
This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain
-
explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group