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into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical infrastructure, on-campus children's day care and sports
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segmentation, target detection and change detection along and across multiannual series of data. Methodologies like foundational models, machine learning, deep learning, multitask learning, enforcement learning
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techniques and machine learning algorithms. The goal is to decipher patterns in the bioelectrical signals. Project UID-50008-2025 funded by FCT-Fundação para a Ciência e a Tecnologia. Scientific Area: Basic
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/e we challenge you to take charge of your own learning process . An excellent technical infrastructure, on-campus children's day care and sports facilities. Unlimited access to the modern on‑campus TU
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 5 days ago
17 Apr 2026 Job Information Organisation/Company Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID Department DRH Research Field Engineering » Civil engineering
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methodologies — including gamification strategies, adaptive interfaces, explainable AI techniques, and personalized interaction models — to support incremental learning, long-term engagement, and responsible
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. You have experience in machine learning applied to sensors. LanguagesENGLISHLevelExcellent Research FieldEngineering » Electronic engineeringYears of Research Experience4 - 10 Additional Information
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efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices. Still, many challenges are ahead
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Predoctoral Researcher (PhD Candidate) in Computational Simulation and AI for Therapeutic Ultrasound
. Where to apply E-mail oficinadeproyectos@fundacionhm.com Requirements Research FieldEngineering » Biomedical engineeringEducation LevelMaster Degree or equivalent Skills/Qualifications • Master’s degree
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annual vacation pay of 8%. High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process