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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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will involve developing deployable prototypes, efficient big data algorithms, and publishing in top-tier venues in databases, machine learning, and data mining. Key responsibilities will include
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-based hail climatology for France, Switzerland and Northern Italy, including hail swaths per event across more than a decade. Design, develop and train geostationary satellite-based hail algorithms using
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frameworks (MOFs), and related materials using hybrid classical-quantum algorithms. A key component of the role involves using first-principles methods that capture strong electronic correlations, such as DFT
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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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Project (Next-Generation Solvers for Complex Microwave Engineering Problems). This project aims to design and develop physics-guided, data-driven algorithms that can accurately solve complex microwave
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quantum algorithms formulating industrial problems to make them accessible to quantum algorithms mapping quantum algorithms to specific use cases and applications optimizing algorithms in the context
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- your research will result in deployable system prototypes, cutting-edge algorithms, and publications in top-tier venues. You’ll be part of a collaborative environment that values innovation
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at Griffith University. We are seeking applicants with active research interests in quantum computing, quantum algorithm/software development and applications in decarbonisation who can take full advantage
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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