Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
-
Field
-
making and machine learning, with real-world testing and feedback. The successful applicant will work on decision making for anomaly detection, behaviour analysis and surveillance decisions, under
-
Simulation group to apply classical Molecular Dynamics and Machine Learning approaches for development of a new class of hybrid polyphenol-lipid nanoparticles with tuneable internal structure and exploration
-
for drug discovery. Publishing peer-reviewed research and contributing to industrial software tools. About You To be successful in this role, you will have: A PhD in machine learning, computer science
-
: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and
-
Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT's Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning approaches
-
neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
-
at the RMIT Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT’s Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning
-
criteria • Bachelor-level qualification • Australian driver’s licence and access to a car • Excellent organisational and communication skills • Ability to work independently and collaboratively, adapting
-
Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
. The project is aimed to improve our in-house developed process-based computer model and use it to represent the soil ecohydrological and biogeochemical interactions across various carbon and nitrogen soil pools
-
sampling missions design of machine learning systems for real-time obstacle detection, terrain analysis, and environmental adaptation in extreme environments implementation of multi-constraint optimisation