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of facilitating a robust bioeconomy, the Vermaas lab leverages computational methods such as atomistic or coarse-grained molecular dynamics simulations with both classical and machine-learned force fields to study
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Transform (ECT) and a graph visualization method called Mapper, to extract information about underlying data structures. Using machine learning applied to topological signatures, the successful candidate will
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bioacoustics datasets Experience working with Git or other version control platforms Expertise with machine learning and AI Experience with Bayesian statistical methods Expertise with NetLogo and building agent
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Requirements PhD in Statistics or related field with extensive quantitative methodology training Three to five years of related and progressively more responsible or expansive work experience in research design
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veteran status. Required Degree Doctorate Minimum Requirements PhD in NLP/AI/ML; Experience in designing deep learning models and relevant publication record; Communication skills and team work. Desired
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, imaging, big data, statistics, machine learning, and computational methods applied to biology, regenerative medicine, and bioengineering). The successful candidate will be affiliated with one or more