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observational studies and clinical trials in sickle cell disease, gaining experience in clinical study design, regulatory processes, patient enrollment, data management, and research translation. Also to learn
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that directly relate to this position. The Giger Laboratory in the Department of Cell and Developmental Biology at the University of Michigan Medical School is seeking a highly motivated Scientist to join our
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expert to join a multidisciplinary automated drug discovery lab developing technologies to improve ecosystem health. The candidate will support tissue culture, cell culture, cell imaging, multi-omics, live
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University of California, Los Angeles | Los Angeles, California | United States | about 12 hours ago
and labeling methods, best ways to ship materials Ability to teach and assess progress of students learning new lab skills Ability to maintain accurate laboratory records Background knowledge of cell
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, please contact Lisa Peterson, HR Specialist, in the School of Nursing at lispete@umich.edu. Modes of Work Mobile/Remote: The work requirements allow for the majority or all the work to be completed offsite
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cutting-edge genome editing and single-cell approaches in cell lines and in patient samples. The research group is led by Mikko Myllymäki, MD, PhD and our research group is located at the Institute
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Visiting Scholar to acquire additional experience and training, as well as to exchange scientific knowledge in the conduct of cardiovascular research within Physiology and Cell Biology; plans and develops
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states and the transcription factor combinations that drive them as well as predict new combinations with machine learning approaches. This project will encompass: analyse single-cell and multi-omics
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technology (PAT) adds cost, time, and introduction of human error. This project aims to develop a novel, label-free microbial detection method, coupled with machine learning tailored for cleaning validation
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algorithms for asthma. The methods to be employed will include cell culture, transcriptomics, proteomics, multiplex assays, flow cytometry, and machine learning. This project combines expertise in cell biology