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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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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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process and the results obtained. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - To contribute to the specification and development of algorithms for optimizing energy systems with
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optimize reimbursement claims with health insurers. The solution will be based on advanced hyper automation and generative artificial intelligence techniques, focusing on efficiency in terms of performance
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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
systems; - experience in applying Artificial Intelligence/Machine Learning and/or optimization algorithms to wireless networking systems.; Minimum requirements: The four Research Initiation Grants to be
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the system to identify external disturbances and adapt the control parameters to optimize the precision, stability, and safety of the manipulation. Furthermore, the aim is to develop a modular architecture
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written) ; - Fluency in Portuguese (spoken and written) Minimum requirements: - Experience in electricity markets - Experience in developing optimization problems with GAMS - Skills for conceptualizing
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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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to optimize phenotype/physiological space through mechanistic diagnosis and simulations; - Develop an AI-driven platform that fuses SB and real-time field spectral data to advance precision viticulture