43 experiment-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Utrecht University in Netherlands
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PhD: Mixing in turbidity currents in experiments and submarine canyons Faculty: Faculty of Geosciences Department: Department of Earth Sciences Hours per week: 36 to 40 Application deadline: 2
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experiments that will reveal the physical mechanisms of transport and burial of microplastics and POC in turbidity currents down submarine canyons; incorporate these mechanisms into an existing computer model
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will design, execute, and analyze single-molecule experiments using optical tweezers and confocal fluorescence imaging, building on previous work (O’Brien et al., Nat Comm 2024). Together with our
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science, spatial analytics, or a related field; experience with diverse spatial analytical methods; strong programming skills (e.g., Python) and version control (e.g., GitHub); experience working with multi
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AI chatbots changing the ways men seek and experience mental health support? In this I-Heal project, you will investigate this question through qualitative research with men living in disadvantaged
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and students, you’ll apply mathematics to tackle societal challenges and bring new data-driven modelling, experiment, and computer-aided mathematics into education. We welcome applicants from all areas
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fluxes and acidification in global marine P cycling through a combination of field work in the North Atlantic Ocean, laboratory experiments and numerical modelling. A scientific cruise with our research
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development of more junior researchers. Experience in climate education and communication is not essential, but would be an advantage. Requirements: You hold a PhD in psychology, education, communication
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PhD, you will: perform large-scale potato experiments using 100 contrasting soil microbiomes; use automated high-throughput phenotyping to quantify plant growth, physiology and disease development
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field; • strong hands-on experience with deep learning and modern representation learning, preferably including transformers, self-supervised learning, foundation models, autoencoders or related