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be duly proven at the time of hiring. 2; 3. Preferred requirements: Experience using Machine Learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating
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-computer interaction (UX), and/or appli cation of Machine Learning. • Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams. Financial component
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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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for 1 research grant within the framework of project “Understanding Machine Learning Systems”, financed by Faculdade de Engenharia da Universidade do Porto, under the following conditions: Scientific Area
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Computer Science (or close field) with strong foundations in data management, machine learning, and software engineering. Coursework or projects in NLP/LLMs, information retrieval, knowledge graphs/ontologies, data
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factors: Prior experience in developing algorithms for biomedical image processing (especially aligned with the research group's areas) and machine learning/deep learning techniques. Prior knowledge of data
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), of the Polytechnic of Leiria Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Undergraduate Positions Application Deadline 6 Mar 2026 - 23:59 (Europe/Lisbon
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vision based object detection tools, and reinforcement learning techniques. Additional Information Benefits Monthly Maintenance Allowance: €1,309.64 Funding Entity: Instituto Superior Técnico (IST
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
, financed by national funds through FCT/MCTES (PIDDAC Workplan: The scholarship holder will acquire electrophysiological data (EEG; ECG; EMG) from healthy and/or stroke patients, involving brain-computer
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to provide the supporting documents by the grant contracting stage. 3. Preferential Factors Proven experience with decision support systems based on knowledge bases and machine learning. 4. Work Plan The work