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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
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cell populations using spatial transcriptomics. Mechanisms by which bacteria modulate the tumor microenvironment will be studied using orthotopic mouse models, with a focus on myeloid cell populations
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and the African turquoise killifish to model human cardiovascular diseases, polycystic kidney disease (PKD), and cardiac aging. Our research aims to uncover the molecular and cellular mechanisms
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to regulatory agencies, investors, pharma companies etc. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Develop models
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focused on using spatial profiling and machine learning of human specimens in combination with functional experiments in animal models to understand cancer initiation, progression, and metastasis. We
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PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . Minimum Number of References Required 3 Maximum Number of References Allowed Keywords
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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
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Water Systems Location Moscow Posting Context Statement Develops alternative futures and resilience pathways by translating model outputs into spatial and temporal scenarios for a regional testbed
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and animal models of the disease. The selected candidate will also be responsible for analyzing scientific data, writing manuscripts for publication, and helping with grant proposals to agencies such as
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will commence on October 15, 2024. Applicants should hold a PhD in Computer Science or a related technical field on or before October 1, 2024. The project focuses on conducting cutting-edge research in