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hyperpolarized 13C magnetic resonance spectroscopy, nanodiamond-based quantum sensing of ROS, and advanced label-free optical microscopy to establish robust experimental workflows for studying infection biology
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view of GGR and SRM in the transition to climate neutrality in Europe. The project will conduct world-class research and generate robust, scientific resources for evidence-based policy advice and global
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lead the image processing and computational analysis efforts, developing robust methods to register, segment, and analyse spectral micro-CT data, and — where relevant — advance reconstruction and
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on the synthesis and optimization of a proprietary thermodynamic promoter for gas hydrate–based CO₂ capture. Improve synthesis routes to significantly increase yield, robustness, and reproducibility while reducing
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responsibility for driving scientific coherence and ensuring robust project execution across the consortium. The starting date is May 1st 2026. Job description The successful candidate will play a central
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. You are expected to think creatively, identify innovation opportunities, and enjoy working at the forefront of technology, translating research into robust, practical solutions. Required qualifications
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to have improved projections and more robust estimates of uncertainty. The project provides training and growth opportunities in AI. Candidates who have strong interest in machine learning, but minimal
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to interact and collaborate to develop robust ways to decode single molecule imaging data. Your profile The candidate should hold a PhD in biophysics, chemistry, nanoscience or related subjects and have a
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register data and randomized controlled trials. We collaborate with municipalities, ministries and voluntary organisations to base their social, school and crime prevention interventions on more robust