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early development of the placenta, and a basic understanding or willingness to learn bioinformatics is desired. The candidate should be proficient in, or highly motivated to learn complex 3D culture
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qualitative proteomics Expertise in LC-MS/MS techniques, including eventually post-translational modification (PTM) analysis Proficiency with bioinformatics and statistical analysis tools, especially in R and
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hepatic biology. The project will have translational components. Expertise in liver disease models, matrix biology, bioinformatics and immunology are a plus. The Postdoctoral position is expected to build
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neurodevelopmental contexts. Conduct rigorous data analysis using bioinformatics tools and frameworks to manage, analyze, and interpret transcriptomic data at multiple scales. Collaborate within a large consortium
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-motivated postdoctoral researcher with a strong background in biology and experience in bioinformatics. Experience in multiplex proteomics and sequencing analysis and a track record of effective communication
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genome scientists with researchers in the field of genomics technology and bioinformatics science. The work we do will shape the future of the field of genome sciences and the world. To learn more, visit
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biopesticide development and targeted antimicrobial delivery. The team is interdisciplinary, with expertise in molecular microbiology, structural biology, bioinformatics, and protein engineering, and currently
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pcr and qpcr, plate reader, nanodrop or Qubit), primer design, library prep, cloning experience. A candidate that understands biochemistry and biochemical pathways and use of GC/LC-MS and bioinformatics
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sequencing and bioinformatics, iPSC derived cells, tissue organoids and/or tissue slices, analytical techniques e.g. LC-MS, liquid scintillation, HPLC, MS, NMR. Administrative and Collaborative Skills
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, computer science, bioinformatics, or other related disciplines is required. Strong interest, research background and experience in the methodology research in statistical genomics, machine/deep learning