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Field
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a unique opportunity to contribute to cutting-edge research dissecting how cancer cells interact with their microenvironment in response to therapeutic intervention. Our research team develops and
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deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement
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ideas. To develop algorithms, machine learning models, Python modules, demonstrators and training pipelines for publication and translation into commercial products that can be widely and reliably adopted
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(“Autonomous System for Hybrid Hyperspectral-SAR Monitoring in Precision Agriculture”, Supervisor Prof. Hugo Hernández Figueroa, and “Development of Methodology and Robust Operational Algorithms for Hybrid
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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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Department: Engineering Technology Salary: Commensurate with Experience/Education Description: Possesses, understands, and applies a comprehensive knowledge in area of specialization. Develops
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interpretation is subjective, heavily relying on clinician expertise. This project funded by the Hanarth fund combines ultrasound imaging with histopathology data to train advanced AI models for automatic tumor
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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
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Geospatial Information by offering knowledge, responsible research, open innovation and application services capable of sustaining Cyprus' development. ERATOSTHENES Centre of Excellence aspires to actively
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responsibilities will be to: conduct high-quality research in intelligent sensing and control for complex project environments develop and implement AI-based algorithms (e.g., GNNs, deep reinforcement learning