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to a platform that supports researchers in understanding and analyzing complex respiratory time-series data. You will merge codebases, implement dedicated data containers, port and optimize signal
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PhD candidate on Interprofessional Learning and Team Resilience through the Electronic Health Record
interprofessional care teams in making optimal use of available healthcare information for care optimisation. Your colleagues: You will be based at the Department of Educational Development and Research and the
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communities or living labs). Our studies often take place in the high-tech, health, and educational sectors with the intention to understand, evaluate, and optimize (inter)professional and (inter)organizational
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allocation, safety, and process optimization) Industrial oversight (Ability to guide, monitor, and assess industrial or external partner activities to ensure delivered solutions align with technical
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of all Directorate-level activities and priorities; Plan and coordinate the Director’s agenda, commitments and missions, ensuring alignment with strategic priorities and optimal time management; Maintain
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elements; method validation and platform development: Assisting in the validation of new analytical methods and contributing to the continuous development and optimization of the platform. You will work
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on the results of the Erasmus+ project EDDIE. When it comes to the research part: This PostDoc project explores how artificial intelligence (AI) can be leveraged to optimize energy portfolios for local energy
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design next-generation computer architectures for running large AI models on embedded and edge systems under strict timing, energy, and memory constraints. You’ll explore hardware-aware optimization and co
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(PICs) increasingly used in various applications. To allow a smooth design flow for these PICs, optimized compact models are needed. This PhD position is enabling compact models for optical amplifiers and
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the consequence of selection and the best strategy for recording traits and optimizing selection decisions. For example, breeders must carefully assess risks and the trade-offs of selection for different traits