Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
conservation and spans a range of activities from exploratory analysis, visualization, and discovery to prediction, validation, quantification of uncertainty, and inference. The Statistical Scientist will join a
-
themes: development of innovative tools for single-cell and spatial analysis of lipid immunometabolism (Subprojects 1–5); molecular pathways linking lipid metabolism to immune activation and
-
offshore wind farms or tidal stream arrays. Such wakes are important to understand and predict because of their potential to impact the energy supply from such renewable energy projects. Analysis will be
-
been devoted to these issues within the history of economic thought. Until recently, existing studies have focused primarily on the economic analysis of slavery and on the commercial benefits of empire
-
analysis pipelines and to integrate imaging data into computational models. It is an opportunity to work with research groups across the Cell-Matrix Centre and the Bioimaging Facility. The appointee will be
-
proteomics. Experience with spatial data analysis including multiplex IHC and CODEX. Familiarity executing bioinformatics pipelines in local UNIX/Linux environments and cluster execution (LSF). Proficiency in
-
stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems. The Nelson research group (https://research.fredhutch.org/peternelson/en.html at the Fred Hutch
-
TLDR: Build the data backbone for the next era of AI-powered spatial biology. Please include a cover letter with your application detailing your qualifications and experience for this position
-
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
-
spatial and temporal data analysis using advanced machine learning technologies. The successful candidate will become a part of an interdisciplinary team working to develop machine learning techniques