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Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | 2 months ago
administrative housing data, environmental indicators, and accessibility metrics — and apply advanced spatial methods such as multilevel modelling and geographically weighted regression to identify relevant
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are of interest. The primary objective of this PhD project is to develop adaptive statistical models for marked spatial and spatio-temporal point processes. Many real-world systems exhibit substantial spatial
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analysis and statistical modeling. Experience working with large, complex, and multi-dimensional datasets. Experience with spatial analysis and geospatial data integration, including use of GIS tools (e.g
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Assistant Professor in Marine Biology & Ecology - Biomedical Science or Quantitative Systems Ecology
ecologist working in coastal systems, who applies modern approaches in causal inference, experimental ecology, spatial modelling, and data science, including the use of machine learning to produce rigorous
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PhD researcher in AI:GENOMIX, you will contribute to next-generation models that rethink polygenic prediction and support the future of precision medicine. AI:X is an ambitious initiative at Aalborg
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LiDAR-based ecology. We're looking for candidates with strong technical skills and ecological interest—people who want to use LiDAR, AI, and spatial modeling to advance our understanding of vegetation
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inflammatory systems; applying cutting-edge multi-omics technologies such as single-cell sequencing and spatial transcriptomics to translational research; and developing novel therapeutic strategies and
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for understanding, modeling, designing and implementing innovative nature- and landscape-based solutions for these contemporary challenges. •Would need to have fundamental knowledge on aspects of landscape and urban
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and turbulence gradients in wind tunnels; and new insights for modelling particle-laden turbulent flows in realistic non-homogeneous environments. Location: The PhD will take place at LMFL lab in
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and/or spatial genomics datasets is a plus but not necessary. Proficiency in programming (e.g., Python, R) and familiarity with common bioinformatics tools and packages. A PhD in developmental biology