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FLEX/FFPE), ATACseq, nCounter panels, spatial transcriptomics, ChIP-seq, cut-and-run and others Apply machine learning algorithms to clinical multi-omic datasets. Assist with collaborative and service
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the participation of all health-related programs and create a stronger framework for collaboration and impact among health-related programs. The goal is for the division to boost interdisciplinary learning, enhance
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Biological Science subfield or Medical, Dental, or Medical Science Master’s Degree or Master’s Degree and 18 graduate credit hours in Microbiology, Biological Science, or Medical Science subfield. PhD preferred
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translational microbiome research AI and machine learning approaches for integrative multi-omics analysis and systems modeling Translation of microbiome discoveries into clinically actionable biomarkers and
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Intelligence and/or Machine Learning with one or more of the following areas: Scientific Computing, Modeling, Simulation, Scientific Visualization, or Computational Social Science; Experience developing and
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/Associate/Full Teaching Professor (a non-Tenure-Track faculty position) in Miami with general areas of focus in Application Engineering & Development, Artificial Intelligence/Machine Learning platforms
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research groups focused on molecular biosensing for point-of-use applications. To learn more, visit MOBIUS website at https://mobius.org.au/ The primary objective of MOBIUS is to accelerate the growth
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tools like ViennaRNA and NUPACK) and MD simulations (e.g., with GROMACS). Strong skills in statistical data analysis and machine learning in Python and R are expected, along with experience working in
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methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods. Special
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). Responsibilities Teach two undergraduate courses in Economics (Statistics and Urban Economics) each semester (Fall and Spring); incumbent will not teach more than 3 preparations per year Engage in 1 on 1 and group