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The REACT MSCA DN Project: Self-awareness in humans is an innate capability, arising from the brain’s ability to process a multitude of sensory inputs. Emulating this functionality in electronic
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analysis systems, to ensure safe and trustworthy results. This can involve research questions from NLP and AI like model robustness and guardrails, human-computer interaction such as interpretability and
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research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, and natural language processing. Programming skills, e.g. Python, Java
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social interaction will be facilitated by drawing on action-oriented, engaged methodologies. The methodology ‘Reflexive Monitoring in Action’ will serve as a starting point for interventions. You will also
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or genetics are organized in two focal areas: ‘Molecular Mechanisms of Biological Processes’ and ‘Physiology and Systems Biology’. The ideal candidate must be highly motivated, hard-working, ambitious, creative
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For more information about the position, please contact Dr. Rene Haijema, Associate professor, Rene.Haijema@wur.nl. Questions about the procedure? Get in touch with Jessa Rozema, Corporate Recruiter
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with the option of renewal for another three years; prolongation of the contract is contingent on sufficient progress in the first year to indicate that a successful completion of the PhD thesis within
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opportunities, but you can add even more value with strong quantitative skills and some coding proficiency to accelerate the innovation process and help others leverage your work. As you get going, you’ll gain
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facilitating the retention and transformation of seagrass-exuded DOM and POM into mineral-associated organic matter (MAOM), a process which can facilitate long-term carbon storage. Thus, MPB may enhance MAOM
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-learning energy trading algorithms that are able to cope with these challenges. By leveraging real-time data, developed algorithms continuously adapt to market dynamics and respond to changing market signals