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Field
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sensors or inductive sensors, and demonstrate temperature readout of magnetic nano-objects engineered with high thermosensitivity. For the past 6 years, our team has been developing instrumentation
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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, more sensors, more of the time, we want to understand, what is the minimal data dose of an interactive technology needed to help people build their own knowledge skills and practice to build personal
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and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous PhD project. In addition to electromagnetic geophysics
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for autonomous driving. This project aims to advance the state of the art in visual perception algorithms and real-time systems for autonomous racing, pushing the boundaries of performance, speed, and precision
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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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binding pockets. About the role We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to identify domain functional families
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of classical and hybrid classical-quantum algorithms for treating the correlations. This position offers exciting opportunities for collaboration within UQ, across the QDA network, and with external research
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electromagnetic data during drilling. This includes the further development and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous