Researcher 6, Data Scientist in Food Animal Biology and Production Systems. Located in the G.E.M.S/IAA, a CFANS Interdisciplinary Initiative, St. Paul Campus, University of Minnesota. This is a 12-month, 100% time, annually renewable appointment. The position has research funding by way of MnDrive (Minnesota’s Discovery, Research, and InnoVation Economy). This person will hold an adjunct position in the Department of Animal Science, subject to departmental approval, and will work closely with the Integrated Animal Systems Biology (IASB) Team. Job ID 325017 https://z.umn.edu/AnSciGEMS
DESCRIPTION Optimizing resources in food animal production requires the integration of fundamental, complex biological processes involving numerous nutrition and health interventions with economics and business models to create new knowledge for more effective decision-making. The person in this position is expected to be a core member of the IAA/G.E.M.S team working closely with the IASB. They will also play an essential role in continuing to develop collaborations with faculty in the International Science and Technology Policy and Practice Center (InSTePP), Center for Animal Health and Food Safety (CAHFS), and various current and prospective external partners. Expertise in managing large data sets, machine learning, mathematical modeling, and informatics is essential.
This is a 100% research position. The successful candidate will be expected to:
Work in a team environment to assist in the development of core integrated animal systems biology. 40% Interface with the Department of Animal Science faculty members to determine their data collection, transfer, interoperability, analysis, and sharing needs, propose data analysis models, establish data libraries (metabolites, nucleic acid data on genes and microbes, data on animal physiological responses to diets and diseases), and assist IASB and other Animal Science faculty to integrate data across disciplines in multiple research projects. Assist in development and implementation of analytical platforms for analyzing large-scale data on animal genomics and microbiome, production system productivity interactions involving nutrition, housing systems, environmental impacts, health status, economics, and other biotic and abiotic influences on animal systems. Contribute to ongoing development and maintenance of G.E.M.S.™/IAA ontologies and controlled vocabularies to ensure interoperability of animal systems biophysical data with the other databases in G.E.M.S™/IAA. Strengthen collaboration and networking among members of the IASB team, college and university-wide ag and life sciences informatics, IAA, and external academic, government, and industrial sources of agricultural data and information. 30% Facilitate networking and information exchange among these teams/domains to identify potential research projects and research collaborations. Aid in the analysis and integration of large-scale data sets produced by various sources, and conduct data mining to identify potential patterns that can serve as researchable questions for research proposals. Contribute to joint grant writing efforts among these teams/domains. Coordinate and contribute to writing interdisciplinary publications including journal articles, book chapters, presentations, and online content. 15% Design and assist in the development of apps with easy to use interfaces that aggregate data from micro to macro scales for decision-making involving animal systems. 15%
Essential Qualifications: Ph.D. in data sciences, bioinformatics, animal/biological science or related field. Outstanding capacity to work on the analytics of global (including the U.S.) animal production systems, productivity, and inter-relations to agronomic and crop processing systems in a cross-disciplinary manner to link animal science data and modeling to economics and social outcomes. Excellent skills in computational biology (with an emphasis on genomics, microbiome, nutrition, health, and productivity methods) and biophysical modeling. Ability to efficiently manage large datasets. Compelling written and oral communication skills. Excellent programming skills, and especially demonstrated experience using R or Python. A proven ability to carry out research in a transdisciplinary environment.
Desired Qualifications: Excellent record of publications and prospects for continued professional productivity (encompassing both professional articles and policy outreach material, including web based output) Demonstrated potential for preparing successful grant proposals. Knowledge of and experience working with industry, NGO’s, and government partners.
SALARY AND BENEFITS Salary is competitive and commensurate with the professional experience and qualifications. Fringe benefits include employee health, dental, and faculty life/disability insurance, social security, faculty retirement and opportunities for professional development.
About the Department
The G.E.M.S / International AgroInformatics Alliance (IAA) is seeking to hire an animal science informatics expert to join a highly diverse international and interdisciplinary team of professionals. This position is available August 1, 2017. G.E.M.S / IAA aims to reimagine the relationships between data, institutions, and disciplines to inform and enable innovative agro-economic decisions at different temporal and spatial scales. The overarching goal of G.E.M.S / IAA is to accelerate sustainable productivity growth in local and global agriculture through the development, deployment and stewardship of innovations in food and agricultural systems.
G.E.M.S / IAA is a joint CFANS-MSI catalyzed agroinformatics initiative that makes genomics, environmental, management, and socioeconomic data interoperable at varying spatial and temporal scales to generate actionable information that accelerates and sustains growth in local and global food and agricultural systems. The Alliance (IAA) involves partnerships with strategic entities across UMN and public and private partners around the world.
The IASB team is a leader in food animal production systems biology, and has extensive partnerships with the feed and food animal industries, as well as national and international research collaborations with universities. The mission of IASB is to provide solutions to complex issues in animal productivity, efficiency, environmental sustainability, and well-being. The IASB team uses novel approaches in the animal science field to collect biological information from different layers in the whole animal and animal populations to discover the biological mechanisms that affect animal growth and health responses in commercial animal production systems.
How To Apply
Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach a cover letter and resume.
Additional documents may be attached after application by accessing your "My Activities" page and uploading documents there.
Applicants must submit a resume/CV, cover letter and the names and contact information for three professional references. Incomplete applications will not be considered. References will only be contacted for finalists.
*The search committee will begin reviewing applications on August 2, 2018. The position will reamin open until filled.*
To request an accommodation during the application process, please e-mail email@example.com or call (612) 624-UOHR (8647).
The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.
The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu.
Background Check Information
Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.