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researcher to work with Dr. David Marlevi and co-workers on the use of machine learning and physics-informed analysis for improved hemodynamic risk prediction using four-dimensional flow magnetic resonance
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applicant will take the lead in analyzing multiple projects that involve integrating metabolomics and lipidomics data with other omics (e.g., proteomics, transcriptomics) as well as clinical phenotyping data
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will be to lead and perform experimental work using molecular and cellular biology technique such as siRNA, histology and microscopy, next generation sequencing and cell culture models, conduct data
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inflammatory cytokines in lung disease. The goal is to define mechanisms of relevance to asthma that ultimately may become novel targets for future treatments. The post-doctoral fellow will lead a project to
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research plan and performed in close collaboration with a PhD student. The fellow will work independently and lead this part of the project with freedom to modify the original research plan as needed
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collaboration with a PhD student. The fellow will work independently and lead this part of the project with freedom to modify the original research plan as needed. Ongoing support will be available from the PI
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that will lead to the demise of some neurons while others will remain apparently unharmed. We are also interested in how RNAs/proteins are redistributed into condensates in somas and axons with disease and
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integrate different scientific tools when addressing specific research questions. The Unit of Integrative Epidemiology at IMM is now looking for 2 postdoctoral researchers to lead and coordinate projects as
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to work independently, initiate and lead novel research projects, and prepare high-quality draft manuscripts for research articles is crucial. Applicants must demonstrate an excellent academic track record
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applicant will take the lead in analyzing multiple projects that involve integrating metabolomics and lipidomics data with other omics (e.g., proteomics, transcriptomics) as well as clinical phenotyping data