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Field
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Infrastructure? No Offer Description Mission: Study of cell adhesion and tissue shape change with theoretical and computational models. Functions to be developed: Develop theoretical models. Implement these models
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changes in light, environment and structure switch the function of photoactive systems on and off. We obtain structural information of the different steps of such molecular switches by developing and
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Research area or group: Advanced Electron Nanoscopy (GAeN) Group Description of Group/Project: We are looking for a skilled Postdoctoral Researcher to support advanced characterization efforts within
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. Applicants are invited to propose a research project around the development of AI models for predicting promising catalyst candidates to integrate molecular modelling techniques, experimental data bases and
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researcher will lead, together with Dr. Daniel Montoya and other project members, the development of agroecological models that simulate crop rotations in space and time under a scenario of climate change
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required: The applicant should have a PhD degree in Economics with a solid background in quantitative methods (microdata and macroeconomic modelling) and programming, particularly with the R software
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of twisted quantum materials and two-dimensional correlated electron systems. This project covers a wide range of areas, including advanced van der Waals materials, moire quantum matter, superconductivity
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innovative experiments. The work will include defining and optimizing in vitro models using diverse cell types and advanced platforms, as well as establishing correlations between applied mechanical stimuli
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learning) applied to operational infrared images. Design and test a drone payload for the detection and geolocation of fires in night conditions. Collaborate with modeling teams to integrate observational
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for the processing and analysis of multimodal spatial biology datasets. Design and apply advanced image analysis algorithms for cell segmentation, feature extraction, and debarcoding for lineage tracing. Statistically