Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- Monash University
- Curtin University
- The University of Queensland
- University of Adelaide
- University of New South Wales
- RMIT University
- CSIRO
- Nature Careers
- Queensland University of Technology
- 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
-
MIMIC to real-world electronic medical records from platforms, such as Cerner and Epic. Beyond data engineering, the role includes aspects of data science, such as conducting data analysis, feature
-
This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
-
integrating IoT sensor data, ML algorithms, and energy system modelling / simulation. Develop engineering-based simulations to understand operational impacts on energy output and maintenance needs. Prepare
-
experiments for months before the value of output y is measured for some given input x. This creates an exciting challenge for AI researchers to develop smart algorithms that can find the optimal value of input
-
required. Gather, analyse and document features, epics and user stories Define, analyse and document current and future state business processes using standards such as BPMN, identifying opportunities
-
novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
-
including sprint planning, stand-ups, reviews, and retrospectives. Maintain and update JIRA and Confluence to support agile delivery (dashboards, backlogs, epics, features). Monitor project progress, track
-
queries, and automating data transformations. By combining advancements in natural language understanding, algorithm synthesis, and debugging, the proposed framework will enable developers to efficiently
-
will design quantum-safe threshold encryption and/or authentication algorithms. The expected outcome is the design of methods, techniques and their software prototype to implement quantum-safe threshold
-
derivation of actionable insights. Identify and use suitable technologies, tools and algorithms which can be applied to research/business activities. Work with research group/business area to employ analysis