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include other domain models (e.g. emissions, noise) in collaboration with other researchers. This PhD position is part of the Dutch Aviation Systems Analysis Lab (DASAL), a flagship collaboration between TU
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generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network, human agency means the practical ability to understand AI
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probabilistic modelling, latent-variable methods, and structured unsupervised learning. Research Environment & Collaboration The successful candidate will work at the interface of probabilistic machine learning
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digital learning environments combined with repeated survey measures. A willingness to engage in interdisciplinary collaboration and teamwork. Proficiency in English as the working language of
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to their communities and you may be eligible for an exception to this work arrangement. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more about these options
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. Contribution to the scientific and collaborative research environment in Chemical Engineering group and the ENTEG institute. Where to apply Website https://www.academictransfer.com/en/jobs/364403/phd-position
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directed evolution of biocatalysts predictable by machine learning. As part of the ML-GUIDE team, you will closely collaborate with researchers to identify commonalities and distinct aspects of engineering
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willingness to learn Swedish. A valid driving licence. Personal qualities, including curiosity, initiative, reliability, organisational ability and willingness to collaborate, will be important in the selection
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Investigator. Strong knowledge of qualitative research methodologies and familiarity with participatory research approaches are an asset. During your PhD, you will collaborate with the PI and a postdoctoral
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collaboratively in field and multidisciplinary research settings. The following are desirable: Experience of fieldwork, particularly forest inventories or field experiments. Experience of GIS and spatial data