Skip to content Skip to navigation

Quantitative Research Technician

List Date: 
Tuesday, November 28, 2017
Close Date: 
Friday, December 15, 2017

SUPERVISORS: Dr. Lisa Kerr, Dr. Kathy Mills


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.

Position Description

GMRI is seeking applicants for a full-time Research Technician 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 / North Atlantic marine ecosystems and projecting future population and ecosystem features based on scenarios of climate change, fishing, and other drivers of interest. Projects span a range of analytical approaches; some focus on statistical analyses, while others will develop and test population, ecosystem, and coupled social-ecological models.


  • 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 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


  • 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) and ecological 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
  • Available to start in early 2018

 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, protected resources, or spatial planning 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, resume, and list of three references.  Applications will be reviewed beginning December 15, 2017. Note that you will be navigating away from the GMRI website.  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.