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research in deep learning models for multi-sensor satellite data (e.g. SAR, SMAP) within a large international research project on AI-driven solutions for groundwater management. Expected start date and
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, supported by advanced systems-level modelling and close collaboration with industrial and policy stakeholders. The successful candidate will contribute to the HyperCap research program focused on developing
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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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or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
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quantitative and statistical modelling approaches to biological systems (including crop genetics, host-pathogen interactions, pathogen population genetics, evolutionary biology...). The candidate will work in
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2026 or as soon as possible thereafter. The Post Doc will be connected to ongoing research activities conducted within the area of Sensory and Consumer Science. The candidate is also expected to take
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics
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ecological data collection. The positions focus on improving detection and classification performance of deep learning models applied to millions of images collected in European monitoring programs. Key
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, various inducible, non-pathological, and disease-associated aggregates will be used as model systems. The project will employ biochemical, cell biological, and proteomic approaches. Your job
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modeling. The position is available from 1 May 2026 or as soon as possible hereafter. Job description/research area The postdoc will contribute to a project enhancing cross-disciplinary collaboration by