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with bioinformatics tools and software for data analysis (e.g. Seurat, SquidPy, Bioconductor). Strong understanding of statistical methods and data visualization techniques. Familiarity with spatial
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students at Bsc and Msc level in spatial research methods and sustainability-related topics. At the PhD level, you supervise researchers working on land use science and spatial modelling. You write project
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of Assistant Teaching Professor in Spatial Data Science. The successful candidate will teach and advise students in Penn State’s online geospatial education programs: https://geospatial.psu.edu . This is a 36
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Professor (25260446) Responsibilities: The Department is recruiting one scholar at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics
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across different spatial and temporal scales, from building-level energy demand to district-scale interactions and their integration with wider energy networks. PhD Position in Hierarchical Graph Neural
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Location: Singapore, Singapore 259569, Singapore Subject Area: Sociology / Applied Research Methods, Mixed Methods, Statistics, and Data Analysis Appl Deadline: 2026/01/17 00:00AM (posted 2025/12/22
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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
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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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of multi-modal Foundation Models that integrate single-cell omics with spatiotemporal information. The second position will address the development of a virtual tissue model, exploiting spatial
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statistics of mean and extreme wind events over the Baltic Sea region. Tellus A, 67, 29073. https://doi.org/10.3402/tellusa.v67.29073 Björkqvist, J.-V., Lukas, I., Alari, V., van Vledder, P.G., Hulst, S