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Field
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Algorithmic Categorization”, 2024.07707.IACDC supported by measure “RE-C05-i08.m04 – “Support the launch of a program of R&D projects aimed at the development and implementation of advanced cybersecurity
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of learned robotic policies and such other tasks that are assigned to you. Core Responsibilities: Develop and implement algorithmic solutions for the safety monitoring of learned robotic policies. Create and
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. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data. The PhD position will focus on development a comprehensive and AI-driven platform
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Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods of research, testing and data
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systems, understand the design and development decisions that propagate social biases, and develop theoretical and algorithmic approaches to mitigate them. Key responsibilities include developing bias
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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of learned robotic policies and such other tasks that are assigned to you. Core Responsibilities: Develop and implement algorithmic solutions for the safety monitoring of learned robotic policies. Create and
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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that incorporate photogrammetric error theory, geodetic principles, and spatial analysis methodologies. Develop algorithms and processing chains that assess data quality through metrics such as vertical accuracy