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computing clusters, parallel processing, and data pipelining. Strong analytical and statistical background, with the capability to interpret complex biomedical data accurately. Direct experience handling and
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to build machine learning models in support drug discovery Project management skills to prioritize and organize work across multiple projects in parallel Ability to communicate verbally and in writing with a
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. Among the methods used are high-throughput CRISPR screening, protein deep mutational scanning, massively parallel reporter assays, and genetic manipulation of cell lines and mice. The successful candidate
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parallel tasks and projects. Specific responsibilities: 20% effort: Lab administrative/organizational work - ordering, inventory, keeping track of expenditures, interacting with lab safety, collecting