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, RNAseq analysis, R or Python Strong publication record in peer-reviewed journals Excellent written and verbal communication skills Ability to work independently and in teams Required Application Materials
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: Develop and apply LCMS methods for the qualitative and quantitative analysis of biological samples. Design and conduct experiments, analyze data, and interpret results. Collaborate with faculty, staff, and
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. Proficiency in molecular biology techniques such as DNA/RNA extraction, PCR, cloning, protein analysis, Sequencing. Familiarity with omics data analysis relevant to microbiome-host interactions. Experience
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tumor spatial biology via single cell spatial analysis of the tumor microenvironment. Projects aim to reveal molecular mechanisms of drug resistance based on intercellular and intracellular regulation
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protocols. Provide hands-on technical/operational support for preclinical FLASH irradiation experiments of multiple users in collaborating laboratories Contribute to data analysis, manuscript preparation, and
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the Department and wider Stanford community to establish new techniques and research directions. • Apply and obtain competitive funding. • Employ advanced imaging, spatial analysis, and sequencing-based
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, bioinformatics, molecular biology, toxicology, pharmacology). 2. Proficiency in bioinformatics, programming, and tools for the analysis of large genomic datasets and single-cell dataset, including R, linux, python
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, mouse models, standard molecular biology and biochemistry, FACS/flow-cytometry analysis, genetic manipulation of cells (e.g., CRISPR), and microscopy. Candidates with experience in computational analysis
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for Education Policy Analysis (link is external) and the Education Data Science (link is external) program) develop cultural competencies (via events organized by the Race, Inequality, and Language in Education
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patients and established pipelines for data pre-processing, analysis, and integration (Good et al. Nat Med 2022; In Preparation). We now seek to build generative artificial intelligence (AI) models