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. The PhD (M/F), to be recruited in the context of the ERC StG MULTI-viewCELL, will be working on the development of a new method combining machine learning and biophysical modelling to model embryo
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crane. The successful candidate will build reproducible machine learning pipelines, integrate detections into spatial ecological models, and generate conservation-relevant outputs for regional partners
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Lab aims to reveal how metabolism, oxidative stress, and cell death converge to shape cell fate. For more information about the Henry Lab, please visit: https://thehenrylab.squarespace.com/ For more
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, or agricultural greenhouse gas estimation. Proficiency in working with spatial data and geospatial tools. Interest in science–policy interfaces. What you will do Develop and apply biophysical and economic models
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analysis of spatial-omics and imaging data, developing a framework for simulations, simulating epidemics on social networks, building generative models to improve computation time for simulations, and other
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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on
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. The main activities include: (i) the experimental implementation and characterisation (spectral, spatial and intensity noise) of frequency conversion devices using chalcogenide components/materials (crystals
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their ontogeny and developmental trajectories (https://www.nature.com/articles/s41586-026-10198-z ). The lab’s work transitions between mechanistic studies in experimental models and translational human immunology
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colleagues from FBMH. Areas of current research are novel dose delivery methods (FLASH therapy and spatially fractionated), imaging (using prompt photons and proton CT), high throughput radiobiology
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bright points to solar jets, called spicules. The study will involve mathematical modelling complemented with observational data analysis using high spatial, temporal and spectral resolution solar