21 multiple-sequence-alignment Fellowship positions at Nature Careers in United States
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to intervene the malignancies 3) collaborative analyses of myeloid cancers genomics using high-throughput single-cell sequencing chor high throughput proteomics 4) development of small molecule drugs and PROTAC
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, innovative sequencing and bioinformatics technologies including single cell and spatial transcriptomics, molecular biology approaches using cell-based and animal models, and biomarker studies from patients
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conduct laboratory-based research focusing on multiple myeloma and its precursor conditions. Based on the mission of the lab, the successful candidate will be responsible for identifying novel biomarkers
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: Strong research experience in functional genomics ( TALEN/CRISPR screening, FACS, next generation sequencing library preparation ) and patient iPSC-derived neuron/microglia/astrocyte models and brain
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, we use cutting edge genomic techniques such as duplex sequencing, long-read sequencing, and single-cell DNA and RNA sequencing. We are also actively developing new experimental and computational
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cell sorting, and next-generation sequencing library preparation. Bioinformatics and computer science expertise is a must. Excellent oral and written communication skills and the ability to perform both
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, women’s health, and fundamental life science. Will conduct original and collaborative research aligned with MIT HEALS; participate in programming and community events; engage with faculty, students, and
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in normal intestinal homeostasis and perturbations that drive pathology, including risk for tumor development. Our research combines cutting-edge techniques, including single-cell RNA sequencing
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for completing complex research projects during their Ph.D and significant experience in standard laboratory techniques (next-generation sequencing (such as RNA-Seq, ATAC-Seq, etc.), flow cytometry, PCR, western
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expertise in machine learning and/or Bayesian models is preferred. This position will involve both methodology development and analysis of multi-omic sequencing data, including spatial transcriptomic data