255 computer-programmer-"https:"-"https:"-"https:"-"https:"-"Dr" positions at Monash University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
analytical and problem-solving abilities, advanced computer skills across Microsoft Office and Google Workspace, and experience developing effective administrative processes will be essential. Familiarity with
-
analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
-
methods dealing with model complexity - e.g., AIC, BIC, MDL, MML - can enhance deep learning. References: D. L. Dowe (2008a), "Foreword re C. S. Wallace", Computer Journal, Vol. 51, No. 5 (Sept. 2008
-
senior leaders, community representatives, and academic colleagues. You will demonstrate sound judgement, discretion, and a strong commitment to customer service, alongside advanced computer literacy and
-
Rapid Application Engineer Job No.: 688774 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $110,527 - $121,227 HEW 07 plus 17% employer superannuation Amplify your impact at a world top 50 University Join our inclusive, collaborative...
-
Artificial Intelligence is rapidly transforming healthcare by assisting clinicians in disease diagnosis, prognosis, and treatment planning. While recent advances in deep learning and large language models (LLMs) have significantly improved predictive performance, most existing AI systems remain...
-
-performance computing and geochemical modelling to decipher atmospheric CO2 removal mechanisms over geological timescales. The research involves integrating surface process simulations with tectonic frameworks
-
learning, artificial intelligence, statistical computing, data visualisation, computational statistics, or data science, who are excited to contribute to our world-class research, innovative teaching, and
-
computational techniques can be combined with classical systems to improve performance, scalability, and solution quality for tasks such as: Similarity search and nearest-neighbour queries Graph and routing
-
diverse data sources while addressing the challenges of limited computation, memory, and energy availability at the edge. Leveraging advances in multi-modal deep learning, sensor fusion strategies, and