The Donald Danforth Plant Science Center is recruiting three postdoctoral research associates to join the New Roots for Restoration Biology Integration Institute (NRR-BII), a five-year, NSF-funded initiative supporting integrated research and training activities at the Danforth Center and NRR-BII partner institutions in St. Louis (Missouri Botanical Garden, Saint Louis University, St. Louis Science Center) and beyond (Chicago Botanic Garden, The Land Institute, University of Kansas, University of Missouri, University of Vermont).
Research activities of the NRR-BII focus on the overarching theme of how plant organismal systems (plant roots and shoots) relate to one another, and how those relationships influence and are influenced by plant communities and the soil ecosphere. Land-use conversion has impacted over 75% of lands globally, resulting in a loss of ~50% of the worlds topsoil in the last 150 years. Plants provide the ecological and structural foundation of terrestrial landscapes, building soils and supporting productivity in natural and agricultural ecosystems. Through their root systems, plants connect aboveground components of terrestrial ecosystems to the soil, yet we lack a basic understanding of how plant traits, from roots to shoots, govern these connections. Informed selection of plants based on an understanding of how they interact with each other and with soil will enable restoration of degraded lands in natural and agricultural systems.
The NRR-BII engages researchers from different disciplines (plant organismal systems biology, agro-ecology, community ecology, evolutionary genetics, microbial ecology, restoration ecology, soil science), systems (natural and agricultural contexts), and organizations (nonprofit research institutes, private universities, public universities, land-grant universities, botanical gardens) in a series of tightly coordinated projects targeting multiple representative species from three plant families (sunflowerAsteraceae, beanFabaceae, and grassPoaceae). To facilitate successful completion of proposed projects, NRR-BII supports eight expertise cores that bring together recognized experts in approaches required for the proposed projects: above-ground phenotyping, below-ground phenotyping, data science and analysis, elemental profiling, microbiome characterization, multi-site field logistics, soil structure and composition, synthesis and integration. Scientific advances made by Institute scientists and trainees will improve our ability to predict belowground functional traits from aboveground phenotypes. This information can be applied to accelerate breeding efforts (for perennial crops) and selection of suitably diverse germplasm (for wild species) to use in ecologically and functionally appropriate efforts to restore natural and agricultural ecosystems.
Successful candidates will be co-mentored by at least two NRR-BII Danforth Center Principal Investigators (Miller, Baxter, Gehan, Topp, Fahlgren). Postdoctoral research associates will lead research projects and/or Institute Expertise Cores, and will contribute to ongoing research across the Institute. NRR-BII Institute intentionally sustains a culture of diversity, equity, and inclusion to support, train, and retain the next generation of diverse scientists who can readily integrate across disciplines and develop careers in which they can contribute to the restoration of natural and agricultural ecosystems. Postdoctoral research associates will play a key role in shaping this culture and mentoring Institute trainees.
About the Positions:
We are seeking three postdoctoral research associates, one in each of the general areas listed below. All positions require extensive collaboration among Danforth Center labs and partner institutions, and offer opportunities for leadership of specific projects and/or expertise cores. Specific details and responsibilities of each position will be developed in collaboration with selected candidates.
- Field data collection and analysis. Lead field-based research activities near St. Louis, MO at Shaw Nature Reserve (Gray Summit, MO) and Danforth Plant Science Center Field Research Site (OFallon, MO). Apply root phenotyping approaches for diverse perennial species in the field and greenhouses; integrate root phenotyping with above-ground phenotypes and soil data; use genomic tools to investigate genetic basis of root-shoot covariation.
- Data synthesis. Lead data synthesis including multi-dimensional temporal sequences of above- and below-ground plant phenotyping data, leaf elemental composition data, and soil data; use phenomic/genomic data in a predictive capacity; help oversee one or more expertise cores.
- Phenotyping analysis. Contribute to the development of above-ground in-field imaging via a new phenotyping app, data pipelines and analysis. Help implement app across projects.
Required knowledge, skills, and abilities:
- Creative, collaborative, resourceful emerging leader committed to the restoration of natural and agricultural lands.
- Enthusiastic researcher with a strong work ethic, positive attitude, and willingness to work with large and diverse teams of researchers in a Slack work environment.
- Aptitude for organization and multitasking, capacity to work both independently and collaboratively within a multidisciplinary and interactive research environment.
- Excellent oral and written communication skills; record of peer-reviewed publications.
- Ability to shovel and lift moderate to heavy weights; to stand, bend and lift for prolonged periods of time in summer heat, work to be performed in a hot field and greenhouse (field research postdoc).
- Experience producing and analyzing genomic sequencing data (e.g. GBS, RAD, WGS) using command line programs, previous experience with genome wide association studies (GWAS) a plus (field research postdoc, data synthesis postdoc).
- Experience in multi-dimensional statistical analysis, modeling, and machine learning (field research postdoc, data analysis postdoc).
- Computer science background, experience with image analysis, data extraction, pipeline construction (phenotyping analysis postdoc).