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models. We further propose to develop scalable structure learning methods for these new models, including latent variable identification, and to demonstrate their effectiveness on real data. For this, we
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, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process
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. Ability to accept collegiate responsibilities and act accordingly. Professional command of English and the willingness to learn Dutch Possession of the University Teaching Qualification (BKO
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transport, and device-level performance into a continuously learning model of solar-driven energy conversion devices. The position covers the full life cycle of the Digital Twin, from architecture design and
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(eventually) committees Be committed to obtaining a university teaching qualification, or possessing one already. Where to apply Website https://www.academictransfer.com/en/jobs/362533/assistant-professor-in
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MedTech regions: East Netherlands (The Netherlands) and Emilia-Romagna (Italy). You will work within an international consortium consisting of: University of Twente Assistive Innovations B.V. (https
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» Learning studies Educational sciences » Teaching methods Researcher Profile Recognised Researcher (R2) Application Deadline 17 Aug 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status
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adaptive resource allocation, AI-driven network orchestration, dynamic beam steering, joint communication and sensing, and cross-layer optimization. Machine learning techniques will be investigated
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Materials to Optoelectronic Devices (M2D) group (https://www.m2ngroup.nl
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offers an excellent opportunity to contribute to the national Open Science agenda while advancing research on transparency, reproducibility and responsible research practices. Where to apply Website https