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leading academic and industry partners within the Horizion Europe Project. Your profile We are looking for a highly motivated and talented candidate with a background in deep learning. The required
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the Machine Learning and Artificial Intelligence. Solid mathematical and analytical skills. Knowledge about statistical machine learning, robotic perception, multimodal AI algorithms. Experience in programming
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the challenges of the construction sector and society in relation to the green transition. AM2PM - Additive to Predictive Construction using Learning by Printing and Networked Robots This Postdoc will have an
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analytical skills, scientific curiosity and a clear motivation to work independently while contributing actively to a collaborative research environment. We expect that you have experience with design and
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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competencies You are expected to bring strong analytical skills, scientific curiosity and a clear motivation to work independently while contributing actively to a collaborative research environment. We expect
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: • Develop AI-driven control strategies for grid-forming inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation
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treatment conditions. Development of analytical methods for the analyses of PFAS and their degradation products. Disseminating project results through scientific publications and conference presentations
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processes Insight into processes controlling phosphorus availability Experience with soil phosphorus fractionation techniques, nutrient leaching assessments, sorption isotherm studies or related analytical
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industry-facing research collaboration and coordinate cross-partner workflows in planning, data-sharing, and iterative decision-making across industrial and academic stakeholders. Teach and supervise PhD