Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
of Machine Learning as the problem of approximating function f from the pair of measurements (x,y), and Optimization as the problem of finding the value of input x that maximizes the output y given
-
DNA or RNA motif discovery is a popular biological method to identify over-represented DNA or RNA sequences in next generation sequencing experiments. These motifs represent the binding site of transcription factors or RNA-binding proteins. DNA or RNA binding sites are often variable. However,...
-
This research focuses on developing and evaluating methodologies for the optimal design of control charts within the framework of Statistical Process Control (SPC). The study aims to determine the
-
In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
-
research often overlooks the complexities of mixed-vehicle environments, and the development of optimal deployment, routing, and charging strategies. This project aims to address these gaps by optimising
-
automated recovery algorithms, improving system resilience. Research Areas for Master’s and PhD Students AI-Enhanced Resource Forecasting and Optimization: Research Focus: Developing and testing ML algorithms
-
theoretical colleagues. All research takes place within our dynamic particle physics research group with academics and postdocs, as well as graduate and undergraduate students. Some work will be purely
-
for the role, as determined by the University. Enquiries: Dr Marcus Robinson, Senior Research Fellow, Monash University +61399030128 marcus.robinson@monash.edu Position Description: Postdoc Research Fellow
-
management of laboratory animals, ensuring optimal welfare outcomes while supporting researchers with accurate data and expert technical services. This is a rewarding opportunity to contribute to meaningful
-
compressed into lightweight student models using knowledge distillation, enabling efficient real-time inference on mobile devices. The distilled models will be deployed and optimized on mobile platforms, with