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Pytorch and/or JAX deep learning models. Experience in single-cell or spatial omics data analysis. What we offer Embedding within a computational team, with extensive experience in computational biology and
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will lead research at the intersection of crop-switching, environmental resilience, and agrifood sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling
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they continue to investigate. Approaches include genetics, spatial genomics, single-molecule biophysics, super-resolution imaging, computational modeling, and structural studies including X-ray
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shift a critical part of the spatial and photophysical information into the temporal domain, in order to drastically reduce the number of photons and the acquisition time required for image reconstruction
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to the Institute’s needs. Requirements for candidates: Proven experience in advanced hydrological modeling (e.g., conceptual or physically based spatially distributed models), particularly with SWAT+, SWAT-MODFLOW and
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), environmental epidemiology (M), biostatistics (M), maternal and child health®, biomarkers®, exposure mixtures (I), spatial analysis (I), GIS and mapping (I), toxicology (I), and risk assessment (I) · Advanced
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sequencing instruments into microscopes! Your mission You will join our team, a leading group in the field of DNA nanotechnology specialized in creating molecular tools for life-science research (http
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particular emphasis on its contribution to biodiversity conservation and carbon sequestration under ecological restoration scenarios. The project will integrate spatial analysis, connectivity modelling, and
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approaches from the Digital Humanities. The successful candidate is expected to apply and further develop methods such as spatial analysis, GIS-based research, and network analysis in order to explore
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of Bioinformatics. • Experience in Genomic studies. Functions • Multi-omics data analysis. • Single-cell data analysis. • Spatial biology data analysis. Predoctoral contract. • Reference: PREP2024-002764 • Annual