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Field
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generation of enhancement algorithms tailored for endoscopic videos, with a focus on applications in real-time interventions. Development efforts will prioritize both enhancement quality and computational
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do Quantum computing is an emerging
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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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This post is funded by the ‘Integrating quantum sensors with bespoke quantum error correction’ project supported by the Engineering and Physical Sciences Research Council (EPSRC). The task
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distributions from process-induced microstructure variations using the surrogate models created. Work with the extended team to link the simulation of sensor data with new multi-scale processes for microstructure
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the infrastructure that connects sensors, AI inference systems, large foundational models, and mobile applications. Responsibilities: Design, develop, deploy, and maintain a robust software infrastructure that
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algorithms proficiency in both general-purpose programming (e.g., Python) and scientific computing, with a preference for experience in Julia Experience in writing up research work for publication Highly
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software Replace faulty components (e.g., contractors, capacitors, sensors) Monitor System Performance Check air flow, temperature splits, and system efficiency Log system pressures, amperage, and voltages
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Khani. Job Duties: Developing new models, optimization algorithms, and machine learning algorithms for transportation systems and services (40%). Applying the models and algorithms to new transportation
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learning including reinforcement learning, nature inspired algorithms, deep learning, agent based modeling, and natural language processing. We are specifically interested in research focused