14 algorithm-development-"University-of-Surrey" Fellowship positions at Instituto Pedro Nunes
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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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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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artificial intelligence-based algorithms to optimise operation and predict anomalies in water distribution networks. The algorithms developed should identify patterns and anomalies that indicate the presence
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, design, implement, and validate an optimization system for scheduling group classes within the Koachy platform. The specific goals include: Develop attendance prediction models for different types
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computer vision algorithms to detect clinical interventions performed by nurses and situations of agitation and risk of falling. Volume of data available for the project: Video capture in a hospital
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of Computer Engineering, Engineering Physics, Electrical and Computer Engineering, Physics, or related areas. The goals of the grant are: The main objective of this research grant is to develop a
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grant is to develop and implement key components of a multi-agent system to support mental health care. The intern's responsibilities include: - Implementing the complete architecture of the multi-agent
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of Computer Engineering, Engineering Physics, Electrical and Computer Engineering, Physics, or related areas. The goals of the grant are: Develop, evaluate and integrate: 1. A sub-module for
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Engineering, Engineering Physics, Electrical and Computer Engineering, Physics, or related areas. The goals of the grant are: Contribute to the development of a legal information system by participating in
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Computer Engineering, Physics, or related areas. The goals of the grant are: Design, develop, and validate the web platform and data pipelines that support the end-to-end flow of the digital twin, including