360 computer-programmer-"Multiple"-"Prof"-"U"-"FEMTO-ST-institute"-"O.P" positions at Monash University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
opportunities for people with disabilities. Required knowledge Required knowledge A good knowledge of human-computer interaction is required. The ability and skills to work with people with a range of
-
for Earth" grant by Microsoft, one of only 6 projects in Australia to receive this recognition. The new project will build original frameworks for future applications of Machine Learning and Computer Vision
-
information in the spatial context of the task at hand. To achieve this the computer guidance system needs to be aware of the environment through a rich digital-twin model that is kept up-to-date in the face
-
classification'', Computer Journal, Vol 11, No 2, August 1968, pp 185-194 Wallace, C.S. and D.L. Dowe (1999a). Minimum Message Length and Kolmogorov Complexity , Computer Journal (special issue on Kolmogorov
-
Insects are vital components of natural and agricultural ecosystems that interact with plants in complex ways. Computer simulations can help us understand these interactions to improve crop
-
. Wallace ", Computer Journal , Vol. 51, No. 5 (Sept. 2008) [Christopher Stewart WALLACE (1933-2004) memorial special issue [and front cover and back cover ]], pp 523-560 (and here ). www.doi .org
-
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
-
with Human Computer Interaction research Project funding Project based scholarship
-
The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them using data extracted from software repositories. This fine-tuning process aims to enable the models...
-
This project involves model-based depth of anaesthesia monitoring using autoregressive moving average modelling and neural mass and neural field modelling of the electroencephalographic (EEG) signal. This will be achieved through frequency domain and time domain state and parameter estimation...