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Field
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Learning Develop computer graphics and machine learning algorithms (e.g., SLAM and Gaussian Splatting), and evaluate their accuracy in scene reconstruction and camera trajectory estimation using videos
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Requisition Id 15000 Overview: We are seeking an Associate R&D Staff member who will focus on algorithmic tools for process monitoring, diagnosis, and control. This position resides in the Sensors
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-time reinforcement learning algorithms to personalise training difficulty for the DRUM-AI training app and help shape the future of AI-assisted rehabilitation. The post holder will be based in
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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm
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Driven Discovery. Job Responsibilities: Analyze biomedical data with minimal supervision by performing advanced analysis, algorithm implementation, programming, and quality check. Assist senior analysts
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algorithms and AI methods for hardware security evaluation. The roles of this position include: Study literatures on PCB security evaluation, PCB multi-modal image analysis, and datasheet parsing. Data
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meaning from data. Designing machine learning algorithms and undertaking testing for: predictive maintenance. operational performance and cost optimization. failure prevention and timely reparation of Aids
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. For the development and implementation of new algorithms in the field of 3D model generation, scene design and visual effects and in the development of AR/VR applications, we are looking for committed, independently
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to contemporary challenges while mentoring the next generation of leaders. Building on its strong foundation in Optics and Photonics, EECS is expanding its research into quantum algorithms and their industrial
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Professor positions in Quantum Mathematics with emphasis on pure mathematics with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. The targeted