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through the EU Research Framework Programme? Horizon Europe Reference Number #5131; FCiências.ID/2025/cE3c/20 Is the Job related to staff position within a Research Infrastructure? No Offer Description
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two fully funded PhD studentships starting in August 2026, and we also welcome visiting students and undergraduate interns year-round.Although invisible to the human eye, infrared light is everywhere
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optoelectronic devices with real-world impact. Our lab has two fully funded PhD studentships starting in August 2026, and we also welcome visiting students and undergraduate interns year-round.Although invisible
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 2 months ago
) Positions PhD Positions Country Portugal Application Deadline 6 Nov 2025 - 23:59 (Europe/Lisbon) Type of Contract To be defined Job Status Full-time Offer Starting Date 24 Oct 2025 Is the job funded through
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co-workers. Good communication skills. other skills: computer operation, (Word, Excel, Origin, EndNote, creating graphics, image processing), experimental data processing LanguagesENGLISHLevelBasic
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strong collaborative and programmatic ties with several other departments within (Psychology, Physics, Chemistry-Biochemistry) and outside the College of Sciences (Department Computer Science), College
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PhD programme with equivalent content. PhD required Please note that you must use the University of Alicante's standard CV format https://s.ua.es/es/nSdB for Project-based Research and Technical Staff
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knowledge of machine learning (e.g., in the areas of object detection and identification, generative AI, etc.) Good written and spoken English skills (min. level B2) Good written and spoken German skills (min
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; Machine Learning• Clinical pathways and decision support for patients with acute chest pain• AutoPiX – Explainable Deep Learning for Multimodal and Longitudinal Imaging Biomarkers in Arthritis• Speaking
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are being developed that provide AI-supported tools to identify suitable sources and optimize utilization decisions throughout the product life cycle. Various machine learning approaches are to be used