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temporal scales from seconds to hours and beyond. The aim of this PhD project is to build a multi-scale model linking molecular renewal to functional properties of synapses to study the relationship between
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Neuroscience, or a related field—or an equivalent combination of education and relevant experience. 3+ years of experience fine-tuning spatial transformer networks, contrastive learning, model distillation, RLHF
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-scale atmospheric conditions. Most current regional and global atmospheric chemistry models struggle to represent plume processes. Their spatial resolutions are typically too coarse to resolve plume-scale
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candidate will further train language models to identify and quantify uncertainty in reported impact claims, producing confidence scores for downstream risk modeling. Further, the PhD candidate will identify
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the Department of Human Geography and Spatial Planning (max. 10% of the appointment). Where to apply Website https://www.academictransfer.com/en/jobs/358070/phd-the-urban-ocean-nexus-towar… Requirements Specific
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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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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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. Field campaigns, however, are limited in time and geographic coverage. Satellite observations are thus critical to extend measurements over larger spatial and temporal scales. Yet, satellite retrievals
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Researcher (R1) Positions PhD Positions Application Deadline 30 Mar 2026 - 23:59 (Europe/Stockholm) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research
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Forecasting the Future of Biodiversity: Cutting-Edge Approaches to Population and Community Dynamics
: Applications accepted all year round Details We welcome applications for a PhD in population ecology and demographic modelling within a dynamic, interdisciplinary research group tackling big questions across