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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
in thermodynamics and reaction kinetics. • Background in engineering non-conventional host organisms [e.g., Yarrowia lipolytica]. • Experience with bioinformatics, transcriptomics (RNA-seq
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strands. • Bespoke modelling of tumour metabolic function using 3D and 4D imaging data • Cancer patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics
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leaves durable epigenetic and transcriptional scars that shape long term immunity, inflammation, and lung repair. This position is ideal for scientists excited to combine single cell transcriptomics and
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transcriptomics; and 2) characterize the dimer-specific interacting proteins that mediate differential internalization and trafficking of the various PDGFR dimers in vitro and in vivo . These studies will provide
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spatial transcriptomics Scientific publishing, presentation at international conferences, communitty outreach A little more. A little better. Every day. Your Profile Completed scientific university degree
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disease. Apply and optimize advanced spatial biology techniques, such as spatial transcriptomics, proteomics, and multiplexed imaging, to analyze brain tissue. Lead data analysis and interpretation
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complementary transcriptomic and other relevant omics data, and access, curate and data mine publicly available repositories such as PRIDE. The role will involve close collaboration with research team members
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in plant-soil microbiology, molecular microbiology, or related fields. • Strong knowledge of plant-soil-microbe interactions, nodule and root physiology, metabolomic and transcriptomic analyses
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, proteomic, transcriptomic, imaging, biochemical and/or physiological experiments to elucidate factors critical for important insect traits (digestion, feeding, development, reproduction, DNA repair, etc
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, epigenomics, or transcriptomics Basic experience in computational biology or familiarity with bioinformatics tools (e.g., data analysis pipelines, R/Python, or multi-omic data interpretation) is advantageous