Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
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
-
. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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