Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
analysis in a setting with ample expertise and infrastructure. This is a rare opportunity to develop expertise in quantitative pathology in the burgeoning field of spatial cancer biology. Ours is a diverse
-
laboratory experience, such as: DNA/RNA extraction, PCR, cloning, virus production, ELISA, etc. Computational biology laboratory experience, such as: bulk- singl cell- or spatial-transcriptomic data analysis
-
Supervisor: Dr Guiping Wang Course start date: 1st October 2027 Project details For further information about the research group, please visit our website at https://www.cruk.cam.ac.uk/research
-
nature, heat, air pollution and noise. You will develop and compare residential, mobility-based and trajectory-based measures of environmental exposure, combining spatial analysis with GPS trajectories
-
quantify intraspecific and interspecific interactions, taking into account environmental, spatial and temporal variation. TASKS: The work is based on data analysis and modelling approaches. An initial phase
-
circulating tumor DNA, with comprehensive tissue-based profiling methods such as gene expression analysis, DNA sequencing, single-cell sequencing, and spatial transcriptomics. These high-dimensional data
-
Spatiales"CountryFranceCityPARIS 05 Contact City PARIS 05 Website http://www.latmos.ipsl.fr STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo
-
Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 16 days ago
Scientist (f/m/x) in Spatial Multi-Omics Analysis 103012 Full time, close to full time 27,3 - 39 hrs./week Neuherberg near Munich Partial Home Office possible At Helmholtz Munich, we develop groundbreaking
-
. This 4-5-year project is supported by an NIH R56, the HNC SPORE, and other research funding. The postdoc will investigate the spatial and functional relationships between intratumoral bacteria and immune
-
for: Analysis of bulk and single cell RNA-sequencing, spatial transcriptomics, and proteomics datasets Integration of experimental model data with public and clinical datasets Statistical modeling and survival