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Position Summary The successful candidate will work with Dr. Kunlun Qi < https://kunlun-qi.github.io > on research projects related to kinetic equation and its related multiscale model reduction
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positions, directly supported by TEMPEST, a new National Science Foundation Science and Technology Center, led by Prof. Michael S. Murillo at MSU: https://tempest-stc.msu.edu The successful candidates will
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. The selected candidate will work with Dr. Yuzhen Lu to develop and test automated field-deployed sensing/harvesting systems that may integrate machine vision, artificial intelligence, and mechanisms for
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. Bioinformatics analysis of data will include use of population genomics techniques, phylogenetics and machine-learning development. The successful candidate will be expected to write up results as manuscripts
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Position Summary The TARDIS collaboration is actively applying and extending the Monte Carlo radiative-transfer open-science framework TARDIS (https://tardis-sn.github.io/) to model the physics of
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Computer programming skills Desired Qualifications Experience developing computational tools for biomolecular systems Experience training machine learning models Experience working in a collaborative
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Experience with multivariate ecological statistics or machine learning and GWA Experience with Field research in agronomy or environmental microbiology Experience with gnotobiotic or controlled
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Experience with multivariate ecological statistics or machine learning and GWA Experience with Field research in agronomy or environmental microbiology Experience with gnotobiotic or controlled
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–functional modeling of root system architecture. Phenomics data integration and high-dimensional trait analysis. Predictive breeding and quantitative genetic modeling. Machine learning approaches to
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big-data lake ecology research using techniques from statistics and computer science (e.g., statistical modeling, machine learning, data mining). Knowledge of open science tools (e.g., Github, Zenodo