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Field
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(multiomics), CRISPR genome editing, deep learning, network modeling, confocal and two-photon live imaging. Please visit the Özel Lab Website for more information. Ideal candidates will be highly motivated and
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modeling. Experience in cell culture, molecular cloning, and bioinformatics analyses is required. Proficiency in statistics and programming are highly meriting, especially in gene regulatory networks
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electrophysiology to translational models, including animal studies and analyses of human tissue samples. This full-stack methodology enables us to directly link molecular channel function with disease phenotypes
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tomato and pepper as model systems. Work in Oxford will build on our extensive experience in studying bacterial virulence mechanisms and the role of the plant microenvironment in disease development
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to advancing cancer research and developing new treatments. Our research integrates functional and clinical genomics to uncover molecular mechanisms driving cancer treatment resistance and accelerate
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: Prior background in studying bio-molecular condensates using a combination of biochemistry, fluorescence and quantitative modeling methods is highly desired. Prior backgrounds in single-molecule imaging
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Functions The successful candidate will lead a project investigating the immune-cardiac stroma interphase in heart disease, using a combination of molecular and cellular biology approaches, mouse models
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 27 days ago
Experience Requirements PhD or Equivalent Required Qualifications, Competencies, and Experience Experience in cell culture techniques and/or mouse models. Proficiency in standard molecular biology techniques
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, extension is sought) Contract:TV-L Your tasks Molecular laboratory work with 2D and 3D cell culture models Experimental design, data analysis and interpretation Publishing research findings in peer-reviewed
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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based