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: Conduct field and laboratory activities relating to evolutionary genetics including, but not limited to, sampling, collecting trait data, and extracting nucleic acids from samples. Conduct data analysis
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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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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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computational research projects is required for the proposed research. Expertise in population or evolutionary genetics is preferred but not required. Required skills: · Experience with Python · Experience with
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lab group using behavioral experiments to uncover the quantitative and evolutionary genetics of social behaviors and social dynamics (and sometimes other stuff). Basic Qualifications Qualifications: A
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diseases and their impact on interstate and international trade and community health. They will learn surveillance procedures, diagnostic testing methodologies and algorithms, serological diagnostic methods
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for characterization of CT images. Machine and Deep learning: Develop and implement machine learning and deep learning algorithms to built detection and prediction models for CT images Performance Evaluation: Conduct
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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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