SUPERVISOR: Dr. Andrew Pershing
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.
GMRI is expanding our ability to work with marine ecosystem data of various kinds, to use that data for scientific research, and to develop data products that serve the wider community. To support this work, we are seeking applicants for one or more full-time quantitative research technicians. The technicians will assist with data management, statistical analyses, modeling of fish populations and marine ecosystems, and development of data products to support decision-making in a rapidly-changing ecosystem. 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 beginning in fall 2019.
- 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
- Bachelor’s or Master’s degree in scientific field that included quantitative coursework
- Knowledge of climate science, 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 fall 2019
Other Preferred Qualifications:
- Experience fitting models to data for fisheries stock assessment and/or experience in simulation modeling especially in the context of management strategy evaluation
- 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 (including names and contact information of three references) and resume. The application deadline is July 21, and applications will be reviewed at that time. Note that you will be navigating away from the GMRI website. Questions should be referred to email@example.com. However, we will not accept resumes sent to this address, and 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.