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(broadly defined, from school to the workplace). Demonstrates excellent written and verbal communication skills and use of rigorous, innovative quantitative and/or qualitative methods of analysis. Is
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would include: Co-developing a hybrid machine learning/process-based model of anaerobic digestion processes Performing techno-economic and lifecycle analysis of microgrids build around novel biogas-fueled
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Qualifications: Experience in molecular and cell biology techniques, preferably in single cell sorting (FACS), scRNA-seq, spatial transcriptomics and very strong multi-omic data analysis skills related
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microenvironment architecture that drives cancer progression and therapeutic resistance. The successful candidates will perform spatial omics profiling and analysis to infer biological and clinical insights and
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care providers in identifying and managing patients with referral-warranted oculoplastic disease. Required Qualifications: - MD or PhD with experience in cell culture, data gathering, data analysis
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experience with analysis of large health databases, such as claims or electronic health record data. Required Application Materials: Curriculum vitae Cover letter describing relevant experiences, interests
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bioinformatics tools for data analysis Required Application Materials: Curriculum Vitae Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race
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Bioinformatics, computational analysis is preferable. Excellent communication skills and fluency in spoken and written English. Required Application Materials: Cover letter that describes your research interests
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. Preferred experience in 2P imaging and analysis for cellular migration and GCaMP. Required Application Materials: • CV [including education, research experiences, publications, and previous employment] • A
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-author manuscript with related analysis code and references later during the recruitment process. Stanford is an equal opportunity employer and all qualified applicants will receive consideration without