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Quantitative Research Technician

List Date: 
Wednesday, February 19, 2020
Close Date: 
Sunday, March 29, 2020

SUPERVISOR: Dr. Kathy Mills and Dr. Lisa Kerr


The Gulf of Maine Research Institute (GMRI) pioneers collaborative solutions to global ocean challenges.  Our scientists explore dynamic ocean systems from marine life to environmental conditions to coastal economies. We infuse our discoveries into the policy arena and design solutions with fishermen and seafood business to protect fishery resources, harvest them responsibly, and market them as premium quality food. We share our discoveries with the public and nurture a culture of leadership in communities that depend on the sea. Our education programs cultivate science literacy and build a foundation of collaborative problem-solving among our next generation of leaders, scientists, citizens, and stewards. Each year, we serve over 25,000 stakeholders from Cape Cod to Nova Scotia.

The Gulf of Maine Research Institute is seeking applicants for a full-time quantitative research technician position to assist with statistical analyses and modeling of fish population and marine ecosystem data.  The work will span multiple research projects that focus on understanding changes in the Gulf of Maine and North Atlantic marine ecosystems and projecting future population and ecosystem features based on scenarios of climate change, fishing, and other drivers of interest.  Projects use a range of analytical approaches; some focus on statistical analyses, while others will develop and test population, ecosystem, and coupled social-ecological models. The position will be based in Portland, ME. 


  • Manage large and diverse data sets
  • Conduct statistical analyses (including time series, spatial, and multivariate statistics)
  • Develop and test population, ecosystem, or coupled social-ecological models
  • Manage code for manipulating and processing data in accessible and well-documented manners
  • Perform literature reviews
  • Contribute to the writing of project reports and manuscripts

Other General Responsibilities:

  • Assist with general lab management, including purchasing supplies and equipment, coordinating logistics, and other tasks as needed
  • Contribute to development of project and research team websites
  • Help populate and manage department-wide databases
  • Contribute to efficiency of operations across lab and projects through sharing of skills, codes, and data with other relevant associates

Required Qualifications

  • Master’s (preferred) or Bachelor’s degree in scientific field that included quantitative coursework
  • Knowledge of oceanography, marine ecology, or fisheries science
  • Strong quantitative skills, including experience with statistical analyses (e.g., regression, time series, spatial, and/or multivariate statistics), ecological modeling, and/or simulation modeling
  • Proficient programmer in R
  • Previous experience managing data sets
  • Strong organizational skills and ability to manage multiple tasks and timelines
  • Strong verbal and written communication skills
  • Demonstrated ability to work independently and as part of a team

Other Preferred Qualifications:

  • Experience fitting models to data for fisheries stock assessment and/or experience in simulation modeling
  • Experience working with satellite data or climate model outputs
  • Familiarity with marine fisheries or protected resources in New England
  • Proficient user of Microsoft Excel, Microsoft Access, SQL or other databases, ArcGIS
  • Familiarity with additional programming languages, such as MATLAB, Python, etc. 


To apply for this position, CLICK HERE  to submit cover letter, CV, and three references.  Note that you will be navigating away from the GMRI website.  Applications will be reviewed after the closing date. Questions should be referred to However, we will not accept resumes sent to this address. Incomplete or late applications will not be considered.

We are proud to confirm our long-standing policy and commitment to providing equal access and equal employment opportunities in all terms, conditions, processes and benefits of employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status.  Our employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status.

Applicants and employees are encouraged to voluntarily self-identify their race/ethnicity, gender, disability status and veteran status to assist us in fulfilling various data reporting requirements of the federal government. This self-identification is completely voluntary, will be kept strictly confidential and separate from your application data, and used only to meet federal reporting requirements. Providing or declining to provide this information will not result in adverse action of any kind.