Join our team! Quantitative Research Associate Position

(Posted by Gavin Fay, 20 July 2021)

JOB TITLE: Quantitative Research Associate (Fisheries Science)
Supervisor: Dr. Gavin Fay
Salary Range: $55,000 – $65,000

Overview:
The Department of Fisheries Oceanography at the University of Massachusetts Dartmouth’s School for Marine Science and Technology (SMAST) is seeking applicants for a quantitative research associate in fisheries science to work under the supervision of Dr. Gavin Fay, Associate Professor of Fisheries Oceanography. The research associate will join a team of postdocs, graduate students, and undergraduate researchers applying quantitative tools for sustainable and adaptive fisheries and blue communities in the face of systemic change. The research associate will conduct statistical and ecosystem modeling research and develop decision support tools to support ecosystem-based fisheries management decision-making. They will provide scientific and technical analysis and project leadership for the Fisheries and Ecosystem Management (Fay Lab) research group, and develop a semi-independent research program under the supervision of the UMass Dartmouth faculty member (Dr. Gavin Fay). The successful candidate will be expected to engage and manage in all aspects of the research group including the preparation and submission of grant proposals, report writing, publishing research results, supervising students and research staff, and interacting with industry, funding agencies and collaborators.

The research associate will be expected to work across multiple grant-funded projects. Initial project tasks will include:

  • Lead synthesis of habitat vulnerability frameworks and species narratives for Northeast and Mid-Atlantic marine fish, and develop web-based tools for viewing and interacting with results
  • Contribute to simulation testing of length-based multispecies stock assessment models
  • Develop material for and present at workshops to regional decision-makers and stakeholders on applications of management strategy evaluation to New England groundfish under climate change
  • Co-facilitate stakeholder workshops to determine scenarios for a simulation experiment to evaluate adaptation of fishery independent bottom trawl surveys given spatial overlap with offshore wind areas
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    Research in the Fay lab focuses on developing and testing quantitative modeling tools used for assessment and management of living marine resources, working to advance sustainable decision-making for our oceans and the people who depend on them in a changing world. We focus on decision support tools applied to management of fish, marine mammal, and reptile populations, regionally in the Northeast and Mid-Atlantic of the USA, as well as elsewhere nationally and internationally. A central theme of our work is considering the performance of methods used for management given an ecosystem and socio-ecological system perspective. We use ecosystem and population modeling to test the performance of fishery- and ecosystem-based management strategies and evaluate the robustness of management options to a range of system uncertainty, including climate change. To achieve these goals, we make use of and develop methods for stock and ecosystem assessment, and employ simulation frameworks including Management Strategy Evaluation. To support Integrated Ecosystem Assessment, we are increasingly working across disciplines to integrate dynamics of the human dimension into evaluation of management consequences of choices for human uses of the marine ecosystem. We embrace principles and workflows from open data science to work towards ensuring our work is shareable, accessible, and reproducible. Common to all our work is an applied approach to improve the advice for science-based decision-making by living resource management agencies. We collaborate with scientists at state and federal agencies, international science organizations, and with regional fisheries management organizations. To learn more about working as part of our team, including our lab culture and philosohpy, please read our lab manual. You can find out more about our current research on our website.

    The University of Massachusetts Dartmouth distinguishes itself as a vibrant public university actively engaged in personalized teaching and innovative research, and acting as an intellectual catalyst for regional and global economic, social, and cultural development. UMass Dartmouth’s School for Marine Science & Technology (SMAST) is a nationally and internationally recognized research institution located in New Bedford, Massachusetts; the nation’s top economic fishing port. SMAST’s cutting-edge research projects emphasize interdisciplinary basic-to-applied marine sciences and the development of innovative technologies. The SMAST marine science campus, in collaboration with the Massachusetts Division of Marine Fisheries (DMF), creates a major marine science hub in the Northeast US, bringing together more than 150 faculty, students, and staff engaged in education, research and policy related to commercial fishing, coastal preservation, ocean observation, and climate change.

     
    EXAMPLE OF PRIMARY DUTIES AND RESPONSIBILITIES:

  • Statistical and numerical modeling of fish population and fishery ecosystem dynamics, in single-, multi-species, and ecosystem context for stock assessment and management.
  • Use of simulation frameworks such as Management Strategy Evaluation to test the performance of options for Ecosystem-Based Fisheries Management and scientific monitoring in the context of system change.
  • Develop and apply quantitative tools for evaluating tradeoffs among multiple ocean uses for ecological, economic, and societal objectives, to support Integrated Ecosystem Assessment approaches to Ecosystem Based Management.
  • Advanced statistical analysis of marine fisheries and ecosystem data
  • Plan, facilitate, and participate in stakeholder meetings, leveraging best practices from structured decision making to integrate stakeholder objectives and knowledge for tactical and strategic decision-making for fisheries and coastal communities.
  • Lead design of interactive decision support tools for management and stakeholder engagement processes
  • Use open data science tools to contribute to lab-wide data and management workflow efforts to promote sharing, use, and reproducibility of scientific products, including code repository documentation and management.
  • Synthesize and share results in scientific papers and to industry, management, and at scientific conferences
  • Write and submit proposals for external funding
  • Travel to regional stakeholder meetings, project team workshops, and industry and scientific conferences
  • Coordination of grant funded research projects including budgets, purchasing and reporting
  • Supervise graduate and undergraduate research assistants and technical associates
  • Training of technical staff and students in research computing and statistical methods
  • Interact with industry, federal and state scientific agencies, fishery management councils, and non-governmental organizations
  • Collaborate with mentor(s) to develop and track progress towards an individual professional development plan
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    REQUIRED QUALIFICATIONS:

  • Ph.D. in a relevant discipline, such as fisheries science, quantitative ecology, fisheries ecology, statistics, data science, or another field that demonstrates a strong quantitative background. A relevant MS degree plus appropriate work experience may potentially be substituted.
  • Experience analyzing and modeling marine ecosystems, fishery population dynamics, and/or fishery economics with statistical, economic, and/or simulation models
  • Demonstrated experience and fluency in relevant programming languages, particularly R
  • Strong written and communication skills and excellent organizational ability
  • Demonstrated ability to work independently and as part of a collaborative team
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    PREFERRED QUALIFICATIONS:

  • Stock assessment and Management Strategy Evaluation experience
  • Experience developing tools and interfaces for user access to, and interaction with, data and model outputs
  • Experience with structured decision making, tradeoff analysis, and decision support
  • Familiarity with relevant data sets, including climate model outputs, spatial ocean data, fish and marine ecosystem surveys, and fishery-dependent data
  • Experience working with spatial data and spatial model outputs
  • Experience in and understanding of marine fisheries and fishing communities
  • Engagement with fishery and fishing community stakeholders and decision-makers
  • Presentations and discussions with stakeholder audiences
  • Use of GitHub to collaborate on code and manage projects
  • Experience working in high performance cloud computing environments
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    LOCATION, DURATION, SALARY:
    The position will be primarily located at UMass Dartmouth’s School for Marine Science and Technology in New Bedford, MA. Flexibility exists for remote work, but note that a proportion of the job duties are associated with codeveloping scientific solutions with stakeholders. Further information about the UMass Dartmouth School for Marine Science and Technology and the Fay lab’s research can be found at (www.smast.umassd.edu and www.thefaylab.com).

    The start date is October 1, 2021 or earlier. This is a benefited, full-time position with an initial 1 year contract, with continuation based on performance during the initial year and funding availability. Funding for travel to scientific meetings is available. Research Associates at UMass Dartmouth are covered under the bargaining contract of the Faculty Federation, have PI status (can be the lead investigator on research grants), and are able to serve as the main thesis advisor for students with departmental approval. Salary will be commensurate with experience, with range $55,000 – $65,000.

     
    APPLICATION:
    Interested applicants that meet the requirements should review the Fay lab’s Code of Conduct, as well as the SMAST Code of Conduct and Diversity Statement, then submit an application consisting of a cover letter, CV, writing sample (e.g. journal publication or technical report) and contact information for at least two professional references to the following job posting: http://careers.umassd.edu/dartmouth/en-us/job/505362/research-associate.

    Review of applications will begin on August 10, 2021. Please submit your materials before this date to receive full consideration.

    Questions about the position can be directed by email to Dr. Gavin Fay (gfay@umassd.edu).

    UMass Dartmouth values excellence, diversity, transparency, student-centeredness, accountability, innovation, engagement, collaboration, collegiality and safety. UMass Dartmouth employees and applicants for employment are protected by federal laws, Presidential Executive Orders, and state and local laws designed to protect employees and job applicants from discrimination on the basis of race, religion, color, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, family medical history or genetic information, military service, veteran status or other non-merit based factors. For more information about benefits and working at UMass Dartmouth, view the Human Resources website.