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intelligence algorithms.”, financed by National public entities (IFAP IP), under the following conditions: Scientific Area: Geospatial Engineering Admission requirements: Candidates must meet the following
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to or higher than 16 points. 4. Work Plan: 4.1. The purpose of this contract is to perform the following tasks: Literature review in artificial intelligence algorithms for multi target contexts; Development
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approaches, including machine learning algorithms, for analyzing biological data. Hands-on experience in programming environments like Bash, R, or Python. Solid interpersonal and communication skills and
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solution will utilize information collected through specific sensors installed in the infrastructure, which will be processed by advanced Artificial Intelligence algorithms. The works listed for this grant
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the execution of the following tasks related to modelling the incineration process of the pilot units, with the following main objectives: - development of evolving algorithms based on Machine Learning
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activities will be developed in the Power Electronics area, focusing on programming control algorithms on a Xilinx FPGA. This project aims to implement internal fault tolerance in a power electronics
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, annotating and structuring databases, as well as feature engineering for computational modelling; d) Experience in the development and application of machine learning algorithms to the analysis of biomedical
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algorithms; - Automation of the model customization process by conducting laboratory tests.; - Improvement of the data workflow for real-time processing and sharing.; - Data collection in experimental and real
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learning methods to digital pathology Development of deep learning algorithms for the computational analysis of whole-slide images. The objective is to identify relevant biological features and to perform
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architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve