Hedging of Foreign Exchange Risk (filled)
Postdoctoral Researcher (1 year contract, renewable)
The University of Sydney is a world-renowned university offering the highest quality teaching, learning, and research facilities. Sydney is located on Australia’s south-east coast and features year-round sunshine and the world’s best beaches. The Computer Engineering Lab (http://www.ee.usyd.edu.au/cel/) in the Department of Electrical and Information Engineering is seeking a postdoctoral researcher for a research initiative funded by the Australian Research Council. Applicants should have completed their PhD in machine learning or a closely related discipline.
Financial institutions are required to absorb risks associated with foreign exchange (FX) transactions. This work involves applying recent parallel computing and machine learning techniques to better understand and manage such exposure. An environment is being developed to facilitate the testing of risk management strategies and provide an interface to scalable computational resources. The environment will be used to develop improved techniques for: customer flow and exchange rate prediction, hedging strategies, and FX market models. This research will potentially enable national banks to better quantify and manage risk, allowing them to be more competitive in global FX markets.
Interested candidates should email a resume/CV to: philip.leong_at_sydney.edu.au.
FPGA-based Machine Learning (filled)
Postdoctoral Researcher (1 year contract, renewable)
The University of Sydney is a world-renowned university offering the highest quality teaching, learning, and research facilities. Sydney is located on Australia’s south-east coast and features year-round sunshine and the world’s best beaches. The Computer Engineering Lab (http://www.ee.usyd.edu.au/cel/) in the Department of Electrical and Information Engineering is seeking postdoctoral researchers and PhD students for a research initiative funded by the Australian Research Council and Zomojo Ltd. Applicants should have completed their PhD in reconfigurable computing or a closely related discipline and be interested in machine learning.
This project is focused on the challenge of applying real-time machine learning to massive high-frequency data streams such as those seen in financial markets or internet traffic. We will improve upon current machine-learning techniques and innovate methods for translating computationally complex machine- learning algorithms directly to circuit-based execution. The key will be a hardware-based solution which avoids the overhead delays incurred by software running on a processor. If real-time high-speed machine learning can be realized on a hardware-accelerated platform, the applicability of machine learning applications can be broadened.
Interested candidates should email a resume/CV to: philip.leong_at_sydney.edu.au.
Interfaces for Quantum Computing (filled)
Postdoctoral Researcher (1 year contract, renewable)
The University of Sydney is a world-renowned university offering the highest quality teaching, learning, and research facilities. Sydney is located on Australia’s south-east coast and features year-round sunshine and the world’s best beaches.
The Computer Engineering Lab (http://www.ee.usyd.edu.au/cel/) in the Department of Electrical and Information Engineering is seeking postdoctoral researchers and PhD students for collaborative research with the Quantum Nanoscience Laboratory in the School of Physics. The research will be located in the Australian Institute for Nanoscience, a $110 million building being constructed at the University of Sydney.
We are developing new, scalable methods and hardware to enable large-scale quantum computing. The driver for this major effort is the lack of commercial off-the-shelf hardware well suited to addressing the research challenges posed by quantum science. Research is focused around fast, low dissipation, cryogenic, switching technologies and single chip complete control systems that imbed DACs, ADCs and FPGAs at cryogenic temperatures.
Applicants should have completed their PhD in analogue VLSI design with knowledge of data converters, signal processing or a closely related discipline. Interested candidates should email a resume/CV to: philip.leong_at_sydney.edu.au or david.reilly_at_sydney.edu.au.