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Field
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. Preferred Experience with GWAS, biobanks, or population-scale genetics. Experience with single-cell, spatial transcriptomics, or functional genomics. Experience developing research software for large-scale
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, genomics, or computational analysis of high-dimensional datasets. Experience with one or more of the following: Flow cytometry Single-cell sequencing Spatial transcriptomics Multiplex imaging Bioinformatics
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
cloning/molecular biology, protein engineering and biochemistry, mammalian cell/tissue culture, flow cytometry, next-generation sequencing, transcriptomics, and animal models of disease. This is an
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proteomics, transcriptomics, collected from state-of-the-art microfluidic lymph node on-a-chip systems used to study infection initiation and immune response. The postdoc will be co-mentored by
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arteriovenous malformations, using patient cohorts and surgical specimens together with whole exome sequencing and a range of transcriptomic, epigenomic, and spatial methods. The successful candidate will analyze
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this project is to exploit transcriptomic data sets for the discovery of new therapeutic antibodies. The lab has a very translational focus, running a tech development lab on the EPFL campus and a translational
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cytometry, and microscopy are encouraged to apply. Additionally, previous experience analyzing transcriptomic data is an advantage, as the dry lab (e.g., single cell RNA-sequencing dataset analysis) informs
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integrating transcriptome, chromatin access and transcription factor binding datasets at bulk and single cell resolution with the aim to connect these profiles with the underlying regulatory networks, and
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spatial transcriptomic data. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex
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cells, and their spatial organization within the tumor microenvironment. We use spatial transcriptomics and spatial proteomics, advanced image analysis, and computational approaches to investigate