Postdoctoral Scholar in Arctic Phytoplankton Imaging and Machine Learning Techniques
Position Overview
Organization: Cooperative Institute for Climate, Ocean, and Ecosystem Studies
Title: Postdoctoral Scholar in Arctic Phytoplankton Imaging and Machine Learning Techniques
Position Details
Position Description
About the University of Washington and CICOES:
The University of Washington (UW) is proud to be one of the Nation’s premier educational and research institutions. Our people are the most important asset in our pursuit of achieving excellence in education, research, and community service. UW is in the greater Seattle metropolitan area, with a dynamic, multicultural community of 3.7 million people and a range of natural environments from mountains to ocean. The UW is a community of 80,000 students, faculty and staff including 25% first-generation college students, over 25% Pell Grant students and faculty from over 70 countries.
The Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CICOES) has existed since 1977 for the purpose of fostering research collaboration between UW and the National Oceanic and Atmospheric Administration (NOAA). CICOES’s research is at the forefront of investigations on climate change, ocean acidification, fisheries assessments, and tsunami forecasting.
Position Description:
We are looking for a highly motivated early-career scientist to join our team at the University of Washington and work at the intersection of biological oceanography, plankton ecology and machine learning. The postdoc will use computer vision and machine learning techniques to analyze large volumes of plankton imaging data collected with an IFCB (Imaging FlowCytobot) from surveys in the Bering and Chukchi Seas. A FlowCytobot is an innovative submersible phytoplankton imaging instrument that continuously measures plankton in-situ in the ocean. A core part of the project will focus on developing image classification algorithms which will be used to summarize plankton taxa distribution. The early-career scientist will work with an interdisciplinary team encompassing scientists from the University of Washington and NOAA Alaska Fisheries Science Center. There will be various opportunities to pursue future collaborative projects, acquire new technical and professional skills, and build a broad scientific network, through wider interactions with ocean and data science communities at both UW and NOAA. The postdoc will be eligible to apply for the UW Data Science Postdoctoral Fellowship and interact with members of the eScience Institute. This is a full-time position for an initial two-year appointment.
Specific duties include:
- Build a phytoplankton image library based on species found in Alaskan waters, using publicly shared image libraries and literature in addition to knowledge from the collaborative team.
- Use machine learning and AI techniques to refine algorithms in R, Python and/or Matlab software to identify phytoplankton taxa from imaging data collected using a FlowCytobot on research cruises in the Bering, Gulf of Alaska, and Chukchi Seas.
- Analyze previously collected phytoplankton community image data in relation to physical, chemical and biological oceanographic data.
- Help prepare and deploy the FlowCytobot on future research cruises and participate on research cruises in the Bering and Chukchi Seas.
- Lead and contribute to publications in peer-reviewed journals, presenting at scientific conferences, participating in proposal writing.
- Document progress on tasks and communicate progress regularly with other team members and leadership.
The impact of CICOES’s environmental research is felt by communities all over the world, and a broad variety of perspectives and life experiences is essential to the success of this research. We encourage candidates from groups historically and currently underrepresented in this field to apply. Please read about our commitment to diversity, equity, and inclusion here: https://cicoes.uw.edu/about/diversity/.
Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement unless agreed exclusion criteria apply. For more information, please visit the University of Washington Labor Relations website.
Compensation
The salary range for this position will be $65,508 to $70,908 per year, commensurate with experience and qualifications, or as mandated by a U.S. Department of Labor prevailing wage determination. Other compensation associated with this position may include a moving allowance or a relocation incentive.
Qualifications
Required qualifications:
- At the time of appointment candidates must hold a PhD in oceanography, marine ecology, statistics, or a related field in computational sciences and have no more than three years of total postdoctoral experience.
- A strong background in at least one analytical coding language (Matlab, Python, R, etc.).
- A demonstrated ability to clearly communicate complicated ideas through presentations and peer-reviewed scientific manuscripts.
- Familiarity with phytoplankton ecology and imaging and/or experience applying machine learning methods to scientific problems.
- A demonstrated ability to work with large scientific datasets.
Desired Qualifications:
- Knowledge analyzing large datasets using statistical software such as R, Matlab and/or Python.
- Familiarity and interest working with machine learning techniques, such as for example, random forest, neural network and/or boosted regressions tree analyses.
- Knowledge of phytoplankton ecology, taxonomy and/or biological oceanography.
- Experience with phytoplankton imaging techniques and phytoplankton taxonomic identification is highly desirable.
- Knowledge of arctic and sub-arctic systems.
- Strong organizational skills, attention to detail, and effective verbal and written communication skills.
- Ability to work independently and as part of a team, interacting cooperatively with people from diverse backgrounds and academic levels.
- Interests in climate change science, impacts of changing ocean conditions on marine ecosystem and food web interactions, and large marine ecosystem management applications.
Instructions
Application Instructions
Please submit—through Interfolio— and provide the following: Cover letter, CV, statement of research interests, contact info for three references.
Equal Employment Opportunity Statement
University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, marital status, pregnancy, genetic information, gender identity or expression, age, disability, or protected veteran status.
Benefits Information
A summary of benefits associated with this title/rank can be found at https://hr.uw.edu/benefits/benefits-orientation/benefit-summary-pdfs/. Appointees solely employed and paid directly by a non-UW entity are not UW employees and are not eligible for UW or Washington State employee benefits.
Commitment to Diversity
The University of Washington is committed to building diversity among its faculty, librarian, staff, and student communities, and articulates that commitment in the UW Diversity Blueprint (http://www.washington.edu/diversity/diversity-blueprint/). Additionally, the University’s Faculty Code recognizes faculty efforts in research, teaching and/or service that address diversity and equal opportunity as important contributions to a faculty member’s academic profile and responsibilities (https://www.washington.edu/admin/rules/policies/FCG/FCCH24.html#2432).
Privacy Notice
Review the University of Washington Privacy Notice for Demographic Data of Job Applicants and University Personnel to learn how your demographic data are protected, when the data may be used, and your rights.
Disability Services
To request disability accommodation in the application process, contact the Disability Services Office at 206-543-6450 or dso@uw.edu.
COVID-19 Vaccine Requirements and Information
Under University of Washington (UW) Policy, University-compensated personnel must be fully vaccinated against COVID-19 and provide proof thereof, or receive a UW-approved medical or religious exemption. This requirement will be a condition of any offer associated with this recruitment. For more information, please visit https://www.washington.edu/coronavirus/vaccination-requirement/.