37 Engineering "https:" "https:" "https:" "https:" "https:" "https:" "https:" "DIFFER" Postdoctoral positions in Netherlands
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environment in the heart of Europe. About the Faculty of Science and Engineering (FSE) At the Faculty of Science and Engineering (FSE), we focus on themes such as circularity and sustainability, future
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. Candidates with an MSc in Chemical Engineering, Materials Engineering, or Mechanical Engineering are also welcome to apply, particularly if their thesis work involved soft matter . Experimental Skills
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-wide collaborations such as the TechMed Centre and the Design Lab About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics
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chip integration. Your profile You have a PhD degree in materials science, surface science, applied physics, physical chemistry, nanotechnology, mechanical engineering, or a related field. You have
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chip integration. Your profile You have a PhD degree in materials science, surface science, applied physics, physical chemistry, nanotechnology, mechanical engineering, or a related field. You have
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@utwente.nl ). Screening is part of the selection process Apply now Share this vacancy About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics
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genome data to learn contextual representations of microbes and communities and translate them into predictive models for successful crop microbiome engineering. Your job Plant-associated microbiomes
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challenge as we lack a blueprint that allows for a bottom-up engineering approach. At the same time, there is an experimental bottleneck: the number of ingredients (lipids, amino acids, cell-free gene
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: 2 October 2026 Apply now The Department of Earth Sciences is looking for a highly motivated PhD candidate with an MSc background in Earth Sciences, Civil or Hydraulic Engineering, or other appropriate
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, data science, applied mathematics, physics, electrical engineering, or a related field. You have a solid background in machine learning; experience with deep generative models (VAEs, GANs, diffusion