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required qualifications must be documented on application materials. Required Qualifications: • PhD in Immunology or a closely related biomedical field • Strong scientific knowledge and hands-on experience
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hydrology and computer science. Any previous success in leading and delivering academic deliverables of using machine learning in solving hydrological problems and experience in spurring interdisciplinary
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, immunoprecipitation, cell culture, immunofluorescence, qRT-PCR, western blots, CRISPR knockout, etc. 3. Experiences in epigenetic research-related skills like ChIP-seq, ChIP-qPCR, HiChIP, and ATAC-seq are highly
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: participate in the design, implementation and evaluation of research. Carry out and supervise laboratory experiments. Develop experimental procedures. Collect and analyze data, prepare and present data
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publications in immunology • Strong background in experimental design, statistical data analysis, and data visualization • Prior mentoring experience and capacity for collaborative research across disciplines
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pharmaceuticals to identify which chemical structures are mineralized to fluoride and which lead to formation of persistent fluorinated byproducts. The key tasks will be to run biodegradation experiments with
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have a PhD in environmental engineering, earth or environmental engineering, or related fields, with a background in ecohydrology. Experience in ecohydrological modeling and remote sensing is desired
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of research. -Carry out and/or supervise laboratory experiments. -Develop experimental procedures. -Collect and analyze data. Qualifications Required Qualifications: - Ph.D. or an equivalent degree. Preferred
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in this field, as well as a PhD. Pay and Benefits Pay Range: $75,000 annually; depending on education/qualifications/experience Please visit the Benefits for Postdoctoral Candidates website for more
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techniques) • Perform and modify documented protocols and assays • Maintain laboratory records and compile data on experiments and assays • Interpret and report on experimental results • Perform statistical