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Field
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and usability 2) increase the range of I/O optimizations supported by the library (e.g., deduplication, caching, scheduling) and 3) identify the limitations and required modifications to the platform
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holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: The ADAPQO project aims to develop technology for optimizing queries on data management systems. In this context, the main
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using Learning Algorithms & Dialog Data (S.H.I.E.L.D.)”. They will be required to: (a) develop machine learning models to predict optimal rehabilitation solutions; (b) use AI algorithms to detect
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in the development, validation, and optimization of 3D-printed Ship Hull and Connector System. This includes conducting finite element modeling, ship resistance and stability assessments, as
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on energy-efficient circuit design and software-hardware co-optimization, with exciting applications in graph-based prediction. What we’re looking for: A PhD in Electrical and Computer Engineering or a
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acceleration. We focus on energy-efficient circuit design and software-hardware co-optimization, with exciting applications in event-based vision. What we’re looking for: A PhD/Master in Electrical and Computer
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the mentorship of leading experts in one of the following priority research areas: Research area 1: Intelligent Structural Optimization using Physics-Informed Reinforcement Learning Research area 2: AI-Enhanced
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interface and usability and ; 2) increase the range of I/O optimizations supported by the library (e.g., deduplication, caching, scheduling).; These objectives are fundamental to improving the efficiency
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Title: Mechanistic Investigation on Electric-Bias-Optimized Plasma Catalysis for H2O-CO2 Conversion Project Introduction: Plasma catalysis is emerging as a promising alternative for carbon-dioxide
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and optimize high-frequency magnetic components and resonant power conversion circuits for advanced aerospace power supply applications. In this role, you will collaborate closely with project