442 parallel-computing-numerical-methods-"Simons-Foundation" positions at Monash University in Australia
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
-
field, or substantial relevant work experience Strong analytical and technical skills, including data analysis and effective use of technical methods Excellent organizational skills with the ability
-
of Physics and Astronomy. This position offers an exceptional opportunity to conduct high quality research in the development and application of new transmission electron microscopy methods (STEM and/or TEM
-
strengthened by sound organisational capability and the ability to complete high-volume tasks with accuracy while applying effective technical methods and processes. If you are excited by the opportunity
-
package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
-
Postdoctoral Research Fellow, you’ll play a key role in the discovery of next-generation photovoltaic materials using a state-of-the-art Chemspeed Technologies automation platform, enhanced by AI-guided methods
-
operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
-
With success stories ranging from speech recognition to self-driving cars, machine learning (ML) has been one of the most impactful areas of computer science. ML’s versatility stems from the wealth
-
. This position offers an exceptional opportunity to conduct high quality research in the development of new transmission electron microscopy methods (STEM and/or TEM) and their application to solve important
-
Anomaly detection methods address the need for automatic detection of unusual events with applications in cybersecurity. This project aims to address the efficacy of existing models when applied