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|2025/787 under the scope of the cryptographic development task funded by the Crypto_Chaves project (HPCAS group) Application submission from 28-Oct to 11-Nov 2025 WHO WE ARE INESC-ID (www.inesc-id.pt
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development", project number S1/4.6/E0050, financed by the European Regional Development Fund (ERDF), through the Interreg VI-B Sudoe Programme 2021-2027, under the following conditions: Scientific Area
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call for awarding a part-time (50%) research fellowship (RF) for the development of the platform DB-HERITAGE – Database of construction materials of historical and heritage interest. 3 – Financing source
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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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and optimisation algorithms, focusing on their practical application in the context of the RaceEngineerAI project. Tasks include: - Developing models capable of simulating the behaviour of racing
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. Develop intelligent algorithms that allow cooling systems to be controlled based on sensor inputs, ensuring adaptation to different scenarios and operating conditions; 4. Integrate and validate
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 8 days ago
management from water and energy sensors; Development of algorithms to improve data collection pipelines from water and energy sensors; Analysis of water and energy datasets using AI techniques, including
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and relative position estimation. 3- Design and implement relative localisation and coordination algorithms. 4- Integrate control and communication systems; deal with disturbances and latency. 5
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 2 months ago
the last mile of maritime container Supply Chain Management, through the analysis, development, and implementation of advanced Artificial Intelligence, optimization, and decision-support algorithms within
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available under the following conditions: OBJECTIVES | FUNCTIONS Development and evaluation of machine unlearning algorithms for speech foundation models, including: - Selection and preparation of models and