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understanding the intricacies of plant chemistry and biology. Research in the Nett lab spans multiple, distinct projects that are all unified by the chemistry of plants, including: 1) evolutionary and biochemical
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field. Our work will be at the intersection of stem cell, developmental, and evolutionary biology, so we are particularly interested in candidates with a strong research background in: -Embryonic stem
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is interested in understanding the neural and algorithmic basis of sensory-guided behaviors in terrestrial animals. We have developed behavioral tasks in mice using stimuli and situations
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will be at the intersection of stem cell, developmental, and evolutionary biology, so we are particularly interested in candidates with a strong research background in: -Embryonic stem cells and/or
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Biology, Evolutionary Biology, Microbiology, Epidemiology, Biostatistics, Applied Math, or related field. Strong coding/computing skills. Familiarity or strong interest in the analysis of pathogen genomic
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bioinformatics analysis pipelines for processing RNA-seq, single-cell RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages
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, including experimental design and reinforcement learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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: Experience with developing efficient numerical algorithms and modifying electronic structure DFT or quantum chemistry software (e.g. Quantum Espresso, PySCF, GPAW), fluency with electronic structure theory and