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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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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
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, developing scalable algorithms for system optimization and control, conducting policy-relevant economic analysis, programming following best practices for reproducible research, presenting findings to academic
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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Research Assistant I-Lab will report to a faculty member in the Department of Human Evolutionary Biology. Under specific direction, performs a variety of basic and general laboratory research and clerical
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. Responsibilities include conceptualizing and implementing statistical and structural models, developing scalable algorithms for system optimization and control, conducting policy-relevant economic analysis