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of promising nanoagents. The objective of this doctoral project is to develop an innovative method for sensing and quantifying the hotspot effect in aqueous suspensions of optically absorbing nanoagents, without
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: *Back-end Java development *Front-end UI development *Signal processing algorithm development This position will work on all phases of software application development ranging from requirements gathering
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, including deep reinforcement learning, large language models, and the theory of deep learning. The candidate will develop DRL algorithms for online and off-line tasks, for robotic applications and possibly
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(Task T2.4). Implement algorithms for training with limited data (Task T3.1). Develop prototypes for use cases in Smart Cities (Task T4.3). These tasks are part of the IDEALCV-CM project, reference: TEC
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undergraduates and postgraduates over 100 programmes with a diverse spectrum of courses. XJTLU is entering a new and exciting phase of its development as part of its strategic priorities for the next ten years
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and application of advanced sampling approaches to examine important ecological and behavioral processes in marine ecosystems. Develops and implements automatic tracking algorithm for detecting dynamic
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Welding in Vacuum We are developing a laboratory robotic simulator for testing stud welding in high vacuum (≥ 10⁻³ Pa) for space applications, with future utilization directly in orbit. The system includes
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radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical imaging. Within our research
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for Artificial Intelligence. The position aims to strengthen methodological and algorithmic work on one or more of the following axes: Optimization and learning on very large models and datasets, improving