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properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms for computational chemistry on quantum computers, and applying
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for large-scale and distributed systems. The role focuses on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position
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on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position collaborates with faculty, students, and external partners
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biochemistry, genetics, microbiology, and cell biological approaches. For more information check the Saavedra lab website: https://www.saavedralab.com The successful candidate for this role will join a
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using a variety of cognitive and cognitive neuroscience approaches (e.g. behavioral, psychophysical, neuropsychological, physiological, imaging, pharmacological, genetic, and computational methods
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, biochemical, and genetic studies to identify and characterize novel natural products with antibacterial activity. Develop and optimize screening assays for natural product discovery, including bioassay-guided
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, biochemical, and genetic studies to identify and characterize novel natural products with antibacterial activity. Develop and optimize screening assays for natural product discovery, including bioassay-guided
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About the Opportunity ABOUT THE OPPORTUNITY The Di Pierro Lab is focused primarily on physical genetics. We are broadly interested in the physical processes involved in the translation of genetic
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. One or more of the following is a plus: experience with Chlamydomonas reinhardtii or Arabidopsis thaliana, photosynthesis, high-throughput genetics, computational data analysis, and fluorescence
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, molecular, physiological, and ultrastructural levels by tracing the acquisition of wild-type and genetically modified symbionts and exploring their interactions with the host using microscopic, metagenomic