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. To achieve this, we develop and integrate cutting-edge experimental and computational platforms: Large-cohort single-cell genomics (e.g., TenK10K) generating millions of profiles to map regulatory architecture
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learning and mechanistic modelling, sensor network development, efficient data sorting and processing algorithms, real-time and model predictive control, and transformative applications in the wastewater
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Despite the popularity of providing text analysis as a service by high-tech companies, it is still challenging to develop and deploy NLP applications involving sensitive and demographic information
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Antenna Design: Developing innovative antenna systems compatible with metal detector coils, optimized for tasks such as minimum-metal landmine detection and deep object detection. Low Power, Compact
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On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices, such as face recognition
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privacy constraints, robust solutions are essential. This PhD project will develop methods for building reliable medical imaging models that generalize across distribution shifts without retraining
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environmental sensing. The incumbent will contribute to the development and deployment of real-time correction algorithms and hardware systems, leveraging GLAO technologies in collaboration with ULTIMATE-Subaru
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. This is an exciting opportunity to work within a multidisciplinary team to design, develop, and validate modular frameworks and algorithms for adaptive intelligent systems. The position provides
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these challenges, calling for the development of responsible AI systems that are transparent, trustworthy, and aligned with human values in educational contexts. This PhD project aims to design, develop, and
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fabrication facilities as well as high performance computing (HPC) facilities at QUT. PhD2: Pore-network modelling of reactive transport As a PhD student, you will develop efficient pore-network modelling