68 parallel-computing-numerical-methods-"Prof" Postdoctoral positions at Stanford University
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position to join NIH-funded projects in collaboration with the U.S. Census Bureau's Enhancing Health Data (EHealth) Program that develop new integrated data to improve our understanding of the socio-economic
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at the Majumdar Group at Stanford University The Magic Lab (link is external) in the Departments of Mechanical Engineering and Energy Science and Engineering at Stanford University, led by Prof. Arun Majumdar
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backgrounds trained in chemistry, chemical biology, microbiology, and/or biophysics fields. We have launched a collaborative antibacterial drug design program integrating chemical biology and mechanistic
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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms
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be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including bulk and single-cell RNA-seq, ADT-seq, ATAC-seq, DNA
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disease. Key responsibilities include: (1) Conduct computational methods development and analysis for systems-level understanding of host-immune responses to diseases. (2) Collaborate effectively with a
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analysis of multiple disease-specific datasets and contribute to the development of novel methodologies in this space. The ideal applicant will have a strong background in bioinformatics methods and a keen
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determined pending application date and program needs. Group or Departmental Website: http://flentje.stanford.edu (link is external) How to Submit Application Materials: Submit your application via this link
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therapeutics. We are seeking a highly motivated, collaborative, and independent Postdoctoral Researcher to spearhead a research program within the general areas of protein biochemistry, engineering, and
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are seeking a highly motivated, collaborative, and independent Postdoctoral Researcher to spearhead a research program within the general areas of synthetic genomics and synthetic biology, as