The Department of Statistics and the Department of Agronomy and Horticulture at the University of Nebraska-Lincoln are pleased to recruit candidates for a postdoctoral position in agricultural bioinformatics and modern data management and sharing. This position is supported by the Quantitative Life Sciences Initiative, a university-wide program supporting the integration of the data and life sciences. We are seeking candidates with expertise in crop genetics, bioinformatics, and statistics, who have demonstrated a high level of skill in data management, bioinformatics and computational biology, and FAIR data sharing in the plant sciences.
Duties include the development of a strong research program in bioinformatics, data management and sharing, which contributes to the organizational mission (e.g., Agricultural Research Division, Quantitative Life Sciences Initiative, Department of Statistics, Department of Agronomy and Horticulture, Office of Research and Economic Development). Responsibilities will include (1) developing methods for FAIR data management and sharing in plant genetics and breeding; (2) developing software implementations of FAIR pipelines, and (3) using newly emerging bioinformatic and computational tools for multitype data analysis (e.g., molecular, phenomic).
The Initiative and the Departments of Statistics and Agronomy and Horticulture will support successful candidates to establish effective disciplinary and trans-disciplinary collaborations including integration with existing research groups; connect with stakeholders, agency, and/or industry partners; obtain and leverage external and internal support (grants, fee revenue, etc.) for research and teaching activities; publish in high-quality, high-impact peer-reviewed journals and participate in scientific meetings and other appropriate activities; and translate research-based information into learner-centered products.
The successful candidates will be expected to teach at least one regular course per academic year in bioinformatics and computational biology. In addition, the successful candidates will participate in program and curriculum development, including graduate seminars and workshops.
Minimum qualifications: PhD in Statistics, Bioinformatics, Computational Biology, or closely related field. Experience with one or more data types in plant breeding and genetics and FAIR data principles, as demonstrated by refereed papers, presentations, or other completed projects, e.g., PhD thesis. Computing and methodological skills appropriate to the sharing and analysis of data types with which the candidate has experience.
Preferred qualifications: Demonstrated methodological novelty and creative ability in one or more area of statistics or bioinformatics related to plant phenotyping and plant breeding and genetics. This includes, but is not limited to, Bayesian statistics, image analysis, crop genetics, and prediction using data mining and machine learning techniques. Experience collaborating (including data collection) with subject matter researchers in the general area of agricultural and natural resources. Sophisticated computational skills including data management, data sharing, algorithm design, and coding. Communication skills, written, verbal and otherwise, at a level sufficient to interact easily with a broad range of researchers at UNL, with the academic world more generally, and with the broader Nebraska agricultural and natural resources community.
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