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Field
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laboratory characterisation of astrophotonic components, including designing robust experimental procedures and analysis of data contribute to novel data analysis and/or instrument control code, leveraging
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, pneumonia, and tuberculosis. Functional/ mechanistic validation of regulatory elements and gene networks controlling inflammation, immune memory, and tissue repair will be implemented using CRISPR inhibition
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tissue-specific mutant mouse models to investigate the underlying mechanisms controlling muscle growth and metabolic flux. The projects are multidisciplinary with excellent opportunities for advanced
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neural networks, covering representation, optimisation, generalisation, robustness and reliability, while remaining sufficiently tractable to inform engineering practice. A key objective is to transform
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tissue-specific mutant mouse models to investigate the underlying mechanisms controlling muscle growth and metabolic flux. The projects are multidisciplinary with excellent opportunities for advanced
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. The project focuses on the intersection of deep reinforcement learning, probabilistic modeling, and bio-inspired architectures (such as Spiking Neural Networks) to achieve sample- and energy-efficient robust
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robust acquisition, synchronization, calibration and quality-control procedures across multimodal data streams. Troubleshooting software, hardware, sensors, timing, synchronization, data acquisition and
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the applicable laws and regulations for government employees, including also the Act on Control of the Export of Strategic Goods, Services and Technology, etc. Candidates who, after assessment of the application
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and/or instrument control code, leveraging advances in machine learning and real-time control fabricate robust instrumentation or photonic components for use at 8m-class and future ELT-class
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process intensification, sustainability, and advanced process control, aiming to develop AI-driven frameworks for multi-scale modeling, multi-objective optimization, and predictive control of complex