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), previously called the Joint Institute for the Study of the Atmosphere and Ocean, 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.
CICOES has an outstanding opportunity for a postdoctoral scholar to conduct research at the intersection of machine learning and ocean carbon biogeochemistry. Dr. Brendan Carter and other CICOES scientists will provide guidance to enhance the professional skills and research independence of the Scholar. The Scholar will be mentored also by PMEL scientist and UW affiliate professor Dr. Andrea Fassbender, and will be part of the Carbon Group at PMEL which includes PIs Dr. Adrienne Sutton, Dr. Simone Alin, and Dr. Richard Feely. This has the potential to be a multi-year appointment. The start date is negotiable, but ideally the applicant would begin between September 2021 and May 2022.
The postdoctoral scholar will conduct original research in biogeochemical oceanography focusing on three topics:
1. Generation of new and updated empirical seawater property estimation routines, with which one can translate physical oceanographic measurements (notably temperature, salinity, pressure, and oxygen) into biogeochemical property estimates (e.g., macronutrients and carbonate chemistry parameters). Areas of focus will be incorporating seasonally resolved surface and near-surface measurements for macronutrients and dissolved gases into the training data products, improving how existing routines handle anthropogenic carbon, and increasing the breadth and quality of the estimation approaches with novel machine learning approaches.
2. Moving towards a homogenized and internally consistent pH data product. This will involve working with an ongoing data product creation effort (Global Ocean Data Analysis Project).
3. Developing approaches for data quality control that integrate the algorithms from topic 1 into hydrographic data submission pipelines.
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/.
For questions about the position duties, please reach out to Dr. Brendan Carter at firstname.lastname@example.org. For questions about applying, including potential disability accommodations, please contact Abby Zorn at email@example.com or (206) 543-5216.
A PhD in physical, chemical, or biological oceanography; data sciences and machine learning; or a closely related field
A demonstrated ability to work semi-independently on problems with unclear solutions and still yield meaningful progress/insights
A demonstrated ability to clearly communicate complicated ideas through presentations and peer-reviewed journal articles
Familiarity with machine learning
An understanding of seawater carbonate chemistry
A strong background in at least one analytical coding language (Matlab, Python, R, etc.), and ideally a coding background in or willingness to learn both Matlab (a proprietary language containing most of the legacy code for these efforts) and Python (a freely distributed coding language with strong machine learning capabilities).
A PhD in biogeochemical oceanography or marine chemistry (specifically)
1 or more years of experience coding in Matlab or Python
Experience working with machine learning tools
Experience working with large marine biogeochemistry data sets and data products
Familiarity with ocean storage of anthropogenic carbon and ocean acidification
An understanding of seawater carbonate chemistry analytical methods
Please submit—through Interfolio—a cover letter describing your relevant experience and a CV.
Please include in the cover letter a brief response to the question "What does it mean for you to have a commitment to Diversity, Equity and Inclusion (DEI)? How have you demonstrated that commitment, and how would you see yourself demonstrating it here?
Internal Number: 88977
About University of Washington
Founded in 1861, the University of Washington is one of the oldest public institutions in the west coast and one of the preeminent research universities in the world. The University of Washington is a multi-campus university comprised of three different campuses: Seattle, Tacoma, and Bothell. The Seattle campus is made up of sixteen schools and colleges that serve students ranging from an undergraduate level to a doctoral level. The university is home to world-class libraries, arts, music, drama, and sports, as well as the highest quality medical care in Washington State and a world-class academic medical center. The teaching and research of the University’s many professional schools provide undergraduate and graduate students the education necessary toward achieving an excellence that will serve the state, the region, and the nation. As part of a large and diverse community, the University of Washington serves more students than any other institution in the Northwest.