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the properties of composite, biological networks which consist of stiff filaments and liquid inclusions which arise from liquid-liquid phase separation. We will use a multi-scale approach bridging scales from
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modelling is a valuable tool to revealing the source of UTLS aerosols, the origin of water masses, and formation processes of cirrus particles. Your key responsibilities include: Preparation, operation, and
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laboratory (bio-)chemistry, beamtimes at synchrotrons, data analysis and comparison to expected physics. Due to the complex structure of the composite droplets, we expect emerging effects which can contribute
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are processed through the online application portal: https://uni-goettingen.de/en/532016.html Language requirements Good proficiency in English and/or German is required. Applicants must provide proof
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for part-time employment. Starting date: 14.01.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date
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semesters Beginning Winter semester Application deadline Please visit https://www.uni-muenster.de/Baccara/application/index.html . Tuition fees per semester in EUR None Combined Master's degree / PhD
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Job related to staff position within a Research Infrastructure? No Offer Description PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1
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cirrus clouds in the UTLS, for which Lagrangian modelling is a valuable tool to revealing the source of UTLS aerosols, the origin of water masses, and formation processes of cirrus particles. Your key
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, Sweden) [IRP18] 5D model-based treatment personalization for right-time adaptive proton therapy (KU Leuven, Department of Oncology, Leuven, Belgium) Where to apply Website https://raptor-consortium.com