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sustainability in mechanical product development. A central aspect of this research will be the investigation and development of innovative mechanical design paradigms made possible by the integration
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/mod/aboutand our linkedIn page: linkedin.com/showcase/lmsd-kuleuven/. The PhD will be co-supervised by prof. Varvara Kouznetsova (https://www.tue.nl/en/research/researchers/varvara-kouznetsova ) from
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additional biomarker candidates•Contribute to the development of biomarker panels with diagnostic and/or prognostic potential The ideal candidate will have:•A Master’s degree in biomedical sciences
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fluid. Based on this, an innovative biomarker platform will be rolled out that aims to increase the success rate of early-phase clinical studies and ultimately accelerate the development of an effective
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or equivalent). A publication record is a plus. In-depth knowledge of plant reproductive development and a strong background in plant genetics, biology, and/or crop breeding. Hands-on experience with or a strong
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citation record must be focused on AI; or alternatively (B), machine learning engineers with an AI-focused PhD and demonstrated 2-year industry experience in AI development Applicants must have in-depth
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contributions to the development of robust monitoring and damage assessment tools for complex industrial structures. Applicants having an appropriate background in natural or engineering sciences should be able
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Kulak (https://kulak.kuleuven.be/ ), where you demonstrate active engagement in interdisciplinary collaboration, both internationally and with colleagues on campus, within the faculty, and/or within
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the validation cases and interface development. Present research results at (international) conferences and events. Assist in workshops, dissemination activities, and teaching tasks (for PhD researchers only
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" that adapt to users and spatial dynamics. Across these pillars, your work spans measurement campaigns, wireless experimentation, spatial analysis, prototyping, and the development of participatory design