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transfer; spatial neighborhood/domain analysis; multi‑omic modeling for RNA+protein where applicable. Pipeline automation & reproducibility – 10% Implement/maintain Snakemake/Nextflow workflows with
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Commission we are looking for a Phd candidate to analyze urban trends. Using detailed spatial data, you will analyze changes in the physical manifestation of cities. So, how does the urban area develop because
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, enabling systematic and efficient exploration using modeling and simulation tools.For the full details please check: https://workingat.vu.nl/vacancies/phd-in-reconfigurable-spatial-accelerators
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of multi-scale urban energy infrastructures. The PhD will explore how these models can represent spatial and temporal dependencies in systems, such as building energy demand, district heating and cooling
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single-cell atlases with spatial transcriptomics to understand signaling pathways and gene-regulatory dynamics. Explainable AI (XAI): Ensure models provide mechanistic insights into cancer cell states
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major research center whose academic partners include Université Grenoble Alpes, Grenoble INP – UGA, CNRS, and Inria. The LIG brings together nearly 500 researchers, faculty members, PhD students, and
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Professor who wants to contribute to advance science, teaching and practice at the interface of Biodiversity, Land Use and Spatial Planning. By planning and governance of land use it is possible to halt
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learning, AI, or statistical modeling applied to biological data Experience with genomics, transcriptomics, single-cell and/or spatial omics technologies Proficiency in scientific computing frameworks Strong
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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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at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics. Candidates with a strong background in the development of novel models and original