Postdoctoral Researcher in Ice Sheet Modeling with Machine Learning

The Ice Future Lab in the Department of Earth Sciences at Dartmouth invites applications for a postdoctoral researcher with expertise in ice sheet numerical modeling and machine learning. This is a 2-year full-time position in residence at Dartmouth in Hanover, NH, with start date preferably in June 2025.

The project, focusing on the dynamics of tidewater glaciers in Greenland, aims to develop a more realistic parameterization of calving law by training machine learning models on reanalysis and observational data, thereby advancing our capacity to predict future glacier behavior under climate change. The postdoctoral researcher will work using both traditional numerical method and physics-informed machine learning to improve our understanding of the calving dynamics of tidewater glaciers, with a focus on Helheim Glacier, Southeast Greenland. This position is funded by NASA in collaboration with the NSF HDR Institute for Harnessing Data and Model Revolution in the Polar Regions.

Dartmouth is a research-intensive Ivy League university with graduate programs in the sciences, engineering, medicine, and business. Postdoctoral scholars are supported by the Guarini School for Graduate and Advanced Studies, including their diversity and inclusion initiatives. Dartmouth is committed to academic excellence and encourages the open exchange of ideas within a culture of mutual respect. People with different backgrounds, life experiences, and perspectives make the Dartmouth community diverse, which enhances academic excellence. In addition, we value applicants who have a demonstrated ability to contribute to Dartmouth's diversity initiatives in STEM research, such as the Women in Science Project, the EE Just STEM Scholars Program, and the Academic Summer Undergraduate Research Experience. Applicants should address in their cover letter how their research, teaching, service, and/or life experiences prepare them to advance Dartmouth's commitment to diversity in service of academic excellence.

• A Ph.D. in Earth Sciences, Glaciology, Climate Science, Applied Mathematics, Computer Science, or a related field at the time of starting the position.
• Strong experience in numerical modeling of ice dynamics and/or machine learning methods, particularly with neural networks.
• Proficiency with ice sheet modeling software, and experience working with large geospatial datasets are preferred.
• Familiarity with remote sensing datasets relevant to glacier and ocean studies, as well as skills in data assimilation and model calibration.
• Programming experience in Python, MATLAB, or other relevant languages.
• Strong track record of relevant publications in peer reviewed journals.
• Strong oral and written communication skills.

Major Duties/Responsibilities:

The successful candidate will play a key role in developing a numerical model of Helheim Glacier using the Ice-sheet and Sea-level System Model (ISSM) and employing transient calibration techniques. This reanalysis will serve as a robust dataset, enabling the use of Deep Learning methods-specifically, a Deep Operator Network (DeepONet)-to infer calving front migration based on a combination of ice dynamics and climate forcings.

Key responsibilities include:

• Developing a numerical model to simulate Helheim Glacier over the past 40 years.
• Applying machine learning methodologies to infer relationships between climate forcing, ocean conditions, and glacier dynamics.
• Integrating diverse remote sensing datasets for training the machine learning model.
• Collaborating with project partners, including NASA and NSF research teams.
• Presenting research findings at national and international conferences and publishing results in peer-reviewed journals.

Please submit the following materials electronically via Interfolio.

1. Cover letter, including contact information for three references.
2. CV.

Review of applications will begin on February 1, 2025; applications submitted after this date will be reviewed until the position is filled. Recommendations letters will be requested for finalists only. For questions about the position, please contact Dr. Gong Cheng, (gong.cheng@dartmouth.edu) with "Helheim ice modeling postdoc" in the subject line.