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motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. An awareness of machine learning theory and techniques
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, longitudinal modelling, machine learning and multivariate approaches. Proficiency in programming (e.g., MATLAB, Python, or R), handling large datasets, and working with complex analysis 2 pipelines is an
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Regional Resilience 5.6 National and Allied Military Resilience 6. Methodologies for Mapping and Investigating Security Processes: From Diagnosis to Foresight and Anticipatory Approaches All Topics
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engineeringEducation LevelBachelor Degree or equivalent Research FieldMathematicsEducation LevelBachelor Degree or equivalent Research FieldPhysicsEducation LevelBachelor Degree or equivalent Research FieldComputer
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, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status
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, liability for military service, protected veteran status, affectional or sexual orientation, atypical cellular or blood trait, genetic information (including the refusal to submit to genetic testing), or any
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
engineering Engineering » Other Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline 30 Jul 2026 - 11:59 (Europe/Lisbon) Country Portugal Type of Contract To be defined Job
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices
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a strong background in artificial intelligence and 3D computer vision, with solid programming skills and an interest in 3D data processing (e.g. point clouds and neural scene representations), along
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ReDiLEEP training in response diversity methods, data management, reproducible code, R/Tidyverse, machine learning and AI for ecologists, visualisation, evidence-based policymaking, science-policy