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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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. The postdoctoral researcher will collaborate closely with an engineering team responsible for process integration and prototype development Expected start date and duration of employment This is a 2.5–year position
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. Nature Physics20, 970 (2024)). You will also work on expanding our coherent imaging methodology to look at dynamics and phase switching in materials at the nanoscale (Johnson et al. Nature Physics19, 215
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be used to prepare lamella samples for high resolution cryo-EM imaging and tomography. From AI assisted image analysis, 3D models for key proteins and biomolecular complexes will be fitted into 3D
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our close collaborators in psychology, physiology and neuro-imaging fields. The candidate The successful candidate must have a strong research profile in sensory and consumer science, more specifically
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an experience in technology-assisted monitoring or computational image analysis. Expected start date and duration of employment The position will start in June 2026, with exact starting date as agreed between
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hybrid models that integrate limnological knowledge into machine learning models following the paradigm of Knowledge-Guided Machine Learning (KGML). The position is part of an on-going project
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. This project aims to improve the evaluation of nitrogen losses in cropping systems by analyzing experimental results and carrying out process-based modelling. Additionally, you will apply your research findings
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University. You will have many opportunities to connect with other research partners, and collaborate with PhD and other postdoctoral fellows, in cross-disciplinary collaborations with other research groups