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We are seeking a Postdoctoral Researcher with expertise in data science, statistical ecology, geospatial statistics, or similar fields, to help build a Living Database on pest control funded by the USDA.  Agricultural pests cause significant damage annually, despite ongoing pesticide use which poses significant risks to people and the environment.

The postdoctoral researcher will join a collaborative and interdisciplinary team of faculty and NGO scientists focused on compiling, integrating, and analyzing satellite data, traits data, and data on crop pests and their natural enemies to better co-manage agricultural systems for food production and ecosystem services. Specifically, our multi-institution project (including researchers at University of Minnesota, University of California, Davis, World Wildlife Fund, and SPRING Innovation, along with a broad international network of insect ecologists, remote-sensing scientists, and data scientists) seeks to build an open-source, standardized data platform for pest control analysis and prediction, to enable scientific understanding and the development of decision-support tools to guide land managers and growers.  

This project builds on prior pest-control compilation efforts that resulted in the largest pest database to date (https://www.pnas.org/content/115/33/E7863). Our team’s core goals include: 

1. Expanding the database by acquiring highly replicated data, across space and time, from governments, industry, and academics (e.g., https://doi.org/10.1111/ele.13622).  
2. Supplementing it with life-history-trait data for agricultural pests and Earth observations (EO) of vegetation and climate for georeferenced locations of pest data.  
3. Leveraging the database to predict pest outbreaks and identify farm/landscape-level interventions to comanage landscapes for food production and environmental quality.  
4. Developing the software infrastructure to automate the continued acquisition of insect, trait, and EO data and process these disparate data sources for subsequent analysis. 

The postdoc will be supervised by Nfamara Dampha and advised by Becky Chaplin-Kramer (Principal Research Scientist at UMN and Global Biodiversity Lead Scientist at UMN) and Rich Sharp (Software Architect at SPRING), and will join a large interdisciplinary team and stakeholder network.

This is a two-year appointment; start date is flexible, but ideally as soon as possible. Salary will be up to $65k/yr. 

Principal Duties and Responsibilities 

• 50% - Develop and test spatio-temporal statistical techniques for integrating EO, insect and trait data
• 20% - Acquire and manage insect and trait datasets
• 20% - Collaborate in development of cyberinfrastructure the living database
• 10% - Participate in IonE community, communicate with the coordinated innovation network

Please apply by preparing the following:

• A cover letter discussing your expertise and background, including:
  • Your research interests and motivations for this position
  • how you meet the required qualifications and your interest in this particular position (especially concerning your quantitative skills)
  • examples of how you currently or will in the future integrate diversity, equity, inclusion, and justice as part of your professional work; if you are a person who is part of a group who has been historically excluded, you may choose to instead include any questions you have for us about our anti-racist commitment and culture
• your CV inclusive of education, publications, awards, and research experience, and
• contact information for 3 references (i.e., name, title, organization; URL to biographical sketch or similar; address, phone number, and email address; and relationship to the candidate). References will not be contacted until final candidates have been identified; candidates will be notified prior to contacting references.

Working Conditions

The majority of the work in this position is performed in a general office (or remote/virtual) setting. Some travel to scientific meetings and working groups will be included. We prefer that the incumbent reside locally, but we are willing to negotiate for a fully remote position which will require approval prior to an offer of employment.

The Office of the Vice President for Research (OVPR) and the Institute on the Environment endorses a “work with flexibility” approach that offers a welcoming and flexible work environment where everyone is inspired to do their best. Work location options include working fully remote, partially remote, or entirely in the office and are based on the work of the position. Some on-site work may be necessary for certain positions, even those designated as fully remote. Because we are a land-grant institution that serves the state, the University will continue to- in most cases- expect employees to live in Minnesota.

This position has been designated as up to flexible work profile four. This can include work primarily on-site, work on-site more than 50% of the time, work remotely more than 50% of the time, or (with prior approval) work fully remotely with the exception of required attendance for on-site events (must reside in the U.S.). IonE management retains the right to modify flexible work arrangement agreements on a temporary or permanent basis for any reason at any time.

Required Qualifications

• A Ph.D. in data science, statistical ecology, or a related field.  
• Strong quantitative skills and demonstrated proficiency with Python, including familiarity with hierarchical modeling, machine learning, or other such analytical approaches.  
• Evidence of commitment to diversity and inclusion in science.  
• Strong interpersonal and communication skills and an ability to work both independently and collaboratively with researchers and practitioners from different backgrounds.  
• 4-8 years experience designing, planning, and executing research projects (PhD time can be used as evidence for this experience).  

Preferred Qualifications

• Familiarity with  ecological questions, ideally related to pest management.  
• Active presence in open-source communities or contributions to projects using open-source software collaboration tools such as GitHub.
• Experience from either PhD or 1-2 years outside of a PhD program managing and analyzing Big Data.  
• Demonstrated ability and/or desire to integrate results across interdisciplinary teams.

About University of Minnesota Twin Cities

The University of Minnesota, founded in the belief that all people are enriched by understanding, is dedicated to the advancement of learning and the search for truth; to the sharing of this knowledge through education for a diverse community; and to the application of this knowledge to benefit the people of the state, the nation, and the world.

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