The UB Glacier Modeling Lab has a place for new MS and PhD students this year, to start Fall 2027. We are seeking motivated students with skills in, or interest and motivation in developing skills in, quantitative glaciology, including numerical modeling, data analysis, and remote sensing. My primary goal as a professor is to help my students succeed through growth in thinking capacity, research aptitude, and personal fulfillment in the UB Glacier Modeling Lab.

Work on these projects will be compensated through Research Assistantships and Teaching Assistantships.

We are searching for graduate students to work on the following research positions

1. Evolution of rifts in Antarctic ice shelves (PhD)

Antarctic ice shelves regulate future sea-level rise by restraining the flow of glacier ice into the ocean. The weakening or disintegration of ice shelves may therefore trigger substantial increases in ice discharge from Antarctica. This PhD project will address ice-shelf rifts: kilometer-scale through fractures that grow longer, over years to decades, until they produce large icebergs. This PhD project will investigate the physical processes governing rift initiation, growth, and interaction with the surrounding ice shelf through a combination of satellite observations, geophysical analysis, and numerical modeling. The student will work with remote sensing datasets, including ICESat-2, ITS_LIVE ice velocity products, and visible imagery, to quantify rift evolution and evaluate theories of rift propagation. We seek a highly motivated student with a strong quantitative background including a Master’s degree in glaciology, geophysics, Earth science, physics, engineering, applied mathematics, or a related discipline. Applicants should have experience with scientific programming and data analysis, have or be eager to develop expertise in remote sensing and computational modeling, and be motivated by fundamental questions in how the Earth works. This project requires a Master’s of Science degree.

2. Inferring crevasse depth on the Greenland Ice Sheet using model emulation (PhD)

This PhD project will develop a low-dimensional emulator of an existing numeric model for crevasse size and apply it across multiple glaciological settings on the Greenland Ice Sheet, including the interior where crevasses form, the ablation zone where they deepen, and major outlet glaciers where true crevasse morphology is debated. The student will combine numerical modeling with satellite imagery and other remote-sensing observations to infer crevasse depth from observable surface features such as crevasse length, width, and spacing. We seek a highly motivated student with a strong quantitative background including a Master’s degree in glaciology, geophysics, Earth science, applied mathematics, physics, engineering, or a related field. Experience with scientific programming, numerical modeling, data analysis, deep learning, or remote sensing is desirable, along with an interest in glacier mechanics and ice-sheet change. This project requires a Master’s of Science degree.

3. Fine-scale flow measurements of Helheim Glacier, Greenland (MS)

Helheim Glacier has been the largest source of ice discharge on the Greenland Ice Sheet since 2018. Recent changes in its flow speed, thinning rate, and terminus position suggest that it is approaching a period of rapid change. This project will measure ice flow speed at sub-hourly intervals to infer changes in the subglacial hydrologic network and proglacial / oceanic conditions at the ice front. This requires deploying and analyzing a network of high-precision GNSS receivers across the glacier. The student will install OGRE GPS stations via helicopter, process the GNSS ice-motion data, calculate spatial gradients in the data, and compare these observations with satellite measurements of ice velocity, surface elevation change, and terminus position. The project offers an opportunity for Arctic fieldwork, geodetic data analysis, and scientific interpretation of glacier data. We seek a motivated student with a background in glaciology, geophysics, Earth science, environmental science, physics, engineering, or a related discipline. Experience with GNSS, scientific programming, quantitative data analysis, or other geophysical observations is desirable. The successful candidate should be comfortable working with large quantitative datasets, comfortable preparing and deploying geophysical instruments in an extreme field setting, and interested in conducting computational research.

4. Remote sensing analysis of seasonal ice flow patterns on Helheim Glacier (MS)

Seasonal variations in ice flow may provide a window into the processes that govern the stability of Helheim Glacier. Observations indicate that, from place to place on the glacier, different processes govern seasonal ice flow variations: ocean/terminus conditions, the subglacial system responding to meltwater inputs, and the subglacial system adapting to meltwater inputs. This project will use high-resolution ice-velocity products (spanning the entire satellite era) to map where and when these different ice flow modes occur and whether they change over time. The student will analyze remote-sensing datasets (including ice velocity, terminus position, and meltwater runoff), use emerging techniques to identify spatial and temporal patterns in ice flow, and evaluate hypotheses for the drivers of seasonal ice-flow variability. We seek a motivated student with interests in glaciology, climate science, remote sensing, or quantitative Earth science, and experience or aptitude in programming, data analysis, and the interpretation of large geospatial datasets.