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multimodal AI algorithms for fire, smoke, and hot-work detection by fusing optical, thermal/infrared, LiDAR, RADAR, and gas sensor data under varying environmental conditions. Design computer vision and human
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queries, and automating data transformations. By combining advancements in natural language understanding, algorithm synthesis, and debugging, the proposed framework will enable developers to efficiently
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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segmentation algorithms to segment industrial wrapped objects with limited data Develop algorithms to identify the most reliable segmented objects. Develop algorithms to determine the best grasp pose based
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-of-the-art algorithms for detecting and classifying safe landing zones using computer vision techniques in order to design and develop custom models for detecting landing zones in real-time based on drone
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algorithms for an autonomous surgical robot, as well as the implementation of control algorithms for interaction with deformable environments in a surgical context. The generated trajectory must be generalized
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linearization with limited or imperfect models. Learning-enabled control dynamics Embedding optimization and learning algorithms (e.g., SGD, Bayesian updates) into control design and analysis. Attack-tolerant
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, implementing, and testing algorithms Engaging in scientific exchange with collaboration partners of the project Preparing reports, scientific papers, and presentations Job Requirements: Master’s degree in
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collaboration with the research software engineering team. Visiting other members of the community of Bioimage Analysts around the world, bringing you in touch with the latest algorithms and software tools
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA DELL'ENERGIA ELETTRICA E DELL'INFORMAZIONE | Italy | 9 days ago
joints under transients of load current and voltage; 2) the refinement of an existing comprehensive algorithm developed in Matlab environment for life and reliability modelling of HVDC cables under typical