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of offers available1Company/InstituteLaboratoire "Atmosphères et Observations Spatiales"CountryFranceCityPARIS 05 Contact City PARIS 05 Website http://www.latmos.ipsl.fr STATUS: EXPIRED X (formerly Twitter
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approaches. The PhD will develop and apply optimization-based energy system models to analyse whether spatially coherent urban and energy configurations can be operated efficiently under realistic physical
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Vacancies PhD Position on Fundamental Aspects of the NaAlCl Battery Key takeaways As part of the ~30 Mio€ ‘SLDBatt’ project, the largest R&D project into battery technology for long-term storage
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ovarian cancer. The laboratory has about 15 members that use cutting-edge methods, including spatial proteomics, spatial metabolomics, spatial transcriptomics, 3D organotypic cultures of human tissue, in
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the molecular signatures of proteostasis loss and identify early markers of proteostatic failure. The role combines wet-lab spatial biology with computational approaches. You will work across models and scales
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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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uses cutting-edge techniques including single-cell and spatial transcriptomics, proteomics, super-resolution microscopy, in vivo tracking, mouse models, and human patient tissues and iPS-derived cells
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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