Gulf of Maine Research Institute
The Gulf of Maine Research Institute (GMRI) pioneers collaborative solutions to global ocean challenges. We steward the Gulf of Maine ecosystem and the hardworking communities that depend on it through a mix of science, education, and community programming.
The Gulf of Maine Research Institute is seeking applicants for a full-time quantitative research technician/research associate position focused on statistical analyses and modeling of fish populations and marine ecosystem data. The work will span multiple research projects that focus on modeling the performance of fish, fisheries, and fisheries management under scenarios of climate change, fishing, and other drivers of interest. Work will include interacting with an interdisciplinary team and engagement with fishery stakeholders. Responsibilities and leadership of these efforts will be scaled with the applicant’s skill level.
Responsibilities/Tasks:
- Conduct stock assessment and fish population modeling
- Conduct statistical analyses (including time series, spatial, and multivariate statistics)
- Synthesis and visualization of modeling results
- Manage code for manipulating and processing data in accessible and well documented manners
- Manage large and diverse data sets
- Perform literature reviews
- Contribute to writing of project reports and manuscripts
Other General Responsibilities:
- Project management across an interdisciplinary team.
- Contribute to efficiency of operations across lab and projects through sharing of skills, codes, and data with other relevant associates
- Contribute to development of project and research team websites
- Help populate and manage department-wide databases
- Assist with general lab management, coordinating logistics, and other tasks as needed
Requirements
Required Qualifications:
- A completed (or nearly-completed) M.S. or Ph.D. degree in a relevant discipline, such as Fisheries Science, Statistics, Ecology, or other related field that demonstrates a strong quantitative background.
- Proficient programmer in R
- Knowledge of fisheries science, population dynamics, stock assessment, and fisheries management.
- Experience fitting models to data for fisheries stock assessment and/or experience in simulation modeling
- Strong quantitative skills, including experience with statistical analyses (e.g., regression, time series, spatial, and/or multivariate statistics), ecological modeling, and/or simulation modeling
- 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:
- Familiarity with marine fisheries in New England
- Proficient user of Microsoft Excel, Microsoft Access, SQL or other databases, ArcGIS
- Experience working in GitHub.
- Experience working in high performance computing environment is preferred.
Applications will be reviewed after the closing date. Questions should be referred to jobs@gmri.org. 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.
NOTE: You will be taken to our portal website to complete this action.
Job Details
Posted On: August 25, 2020
Closing Date: Open Until Filled
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