The Libault’s lab has an opening for Postdoctoral Researcher looking to harness their expertise in bioinformatics, computational biology, machine learning, and plant genomics. Our lab seeks to explore and understand the regulatory network of plant genes, their regulation in response to environmental stress at the single-cell level, and the conservation and divergence of these responses between plant species. These discoveries will support the development of new strategies to improve crop traits and performance.
Research Setting Alongside the University of Missouri’s (located in Columbia, MO) excellent research infrastructure to support these lines of investigation, The Christopher S. Bond Life Sciences Center incorporates laboratories and meeting spaces to provide unmatched opportunities for interdisciplinary biomedical science and agricultural biotechnology research. With its expanding research portfolio, we are accepting applications for a Post-Doctoral Research Associate position in plant single-cell computational biology in the Libault Lab.
Primary Responsibilities The selected postdoctoral researcher will have opportunities to use existing and develop new computational resources to: • Analyze, integrate, and interpret single-cell resolution multi-omics datasets, notably by developing innovative analytic approaches such as establishing transcriptomic trajectories and predicting gene networks. • Conduct comparative -omics analyses between crop species. • Develop innovative approaches, including using machine learning tools, to integrate multi-omic datasets, transcriptomic trajectories, and prediction of gene networks.
The selected postdoctoral researcher will also work in close collaboration with other lab members and with external collaborators In addition to the above-described duties, the individual will be expected to accept committee assignments, reporting responsibilities, and other special ad hoc assignments as requested at the administrative unit, college, and/or university level.
Candidates are expected to have a Ph.D. in plant computational biology/genomics, bioinformatics, or a related field is required at the time of hiring.
Candidates will be evaluated on: • Prior knowledge and demonstrated expertise in next-generation sequencing data analysis, computational systems biology, and/or data integration; • The ability to work in a team environment. • A solid knowledge of plant genomics, evolution, gene expression/regulation, and biological networks • Excellent oral and written communication skills with exceptional organizational and time management skills
Durable skills such as leadership, character, collaboration, communication, creativity, critical thinking, metacognition, mindfulness, growth mindset, and fortitude, as well as customer service, confidentiality, integrity, and a commitment to the University values
Dr. Marc Libault is a Professor in the Division of Plant Science and Technology and a member of the Interdisciplinary Plant Group at the University of Missouri-Columbia (USA). He received his Ph.D. degree in 2004 from the University of Paris-Sud in Plant Cellular and Molecular Biology working on the HP1-like protein in Arabidopsis thaliana. In 2005, he joined the University of Missouri-Columbia as a post-doctoral associate to study the symbiotic interaction between the soybean root and the nitrogen-fixing bacteria, Rhizobia. In 2011, as a faculty at the University of Oklahoma, Dr. Libault developed a system biology approach on the root hair cell, a unique plant root cell type involved in the uptake of water and nutrients from the soil and the first cell infected by Rhizobia in legume plants. In 2018, he joined the University of Nebraska-Lincoln, and pioneered the field of plant single-nucleus technologies to analyze the differential use of the genomic information between plant cells. As a professor at the University of Missouri-Columbia, he is expanding the use of plant single-nucleus biology, spatial -omics, and system biology to study various species and stresses including legumes to study their symbiosis with nitrogen-fixing bacteria.
