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- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
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on the development of methodologies and techniques of Evolutionary Computation and Machine Learning. V - Initial grant duration: 3 months V.I - Renewal Possibility: Possibily renewable VI - Funding and financial
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application of statistical Machine Learning tools. WORK PLAN Collaborate in the following tasks of the project: a) Contribute to the design and development of the Life Cycle Assessment (LCA) system; b) Support
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–5): selection of relevant climatic variables and application of statistical modelling and/or machine learning techniques to predict risk. 3) Preliminary validation of the predictive model using
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or related field;* Solid knowledge in machine vision and deep learning (e.g., TensorFlow, PyTorch, OpenCV); Experience in Python programming (focus on libraries for data analysis and AI); Previous
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acquire advanced expertise in navigation models, spatial representation, object representation, and relational knowledge representation, as well as in planning algorithms based on probabilistic models and
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C644914747-0000023 funded by funded by Recovery and Resilience Plan (RRP) https://recuperarportugal.gov.pt/ and Next Generation EU European Funds Application submission from 20-Feb to 06-Mar-2026 WHO WE
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of computational thinking and didactic knowledge in mathematics among future teachers of the Primary School; Prepare and submit scientific articles. Where to apply Website https://www.ipc.pt/bupc/concursos/form
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
, reference no. 2023.18249.ICDT, financed by national funds through FCT/MCTES (PIDDAC Workplan: Development of methodologies and machine learning algorithms for the detection of anomalous behaviors in flow rate
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Number AE2026-0029 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0029.pdf CALL FOR GRANT
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requirements: Experience using deep-learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating on scientific projects. Publications on deep-learning topics. 4. Work Plan