Professor Becker leads an interdisciplinary group to understand problems in surface geochemistry and computational mineralogy, thus there are research opportunities in fields ranging from experimental approaches and computational modeling of actinide geochemistry (U immobilization in the environment, actinide-containing solids under extreme pressure, temperature, and radiation, U/Np/Pu redox processes) to carbonate biomineralization. Other research includes calculating redox processes (including resolving individual kinetic barriers that control kinetics) carbonate and phosphate biomineralization (from environmental applications to processes on teeth). As a part of Mineralogy and Materials Science Research Group, Becker’s group interacts with Radiation Effects and Radioactive Waste Management group, Michigan Geomicrobiology group, Electron Microbeam Analysis Laboratory (EMAL) and Mineral Physics group.
Professor Flanner’s research ambitions lie in understanding large-scale energy transport in Earth’s climate system, with particular focus on the roles of the cryosphere (including seasonal snow cover, glaciers, and sea-ice) and atmospheric aerosols. To approach these topics, his research group applies and develops computationally demanding models of Earth’s global climate system. The team also analyzes large datasets generated by climate models and satellite measurements, spanning numerous dimensions of space, time, spectrum, and state. Flanner’s group strives to improve climate models by developing numerically efficient algorithms for microphysical processes that occur on scales too small to represent explicitly in global climate models, such as crystal growth in snowpack and interaction of sunlight with aerosols and ice crystals. The group also informs climate mitigation discussions by applying climate models to estimate the perturbations to Earth’s radiation field caused by emissions of short-lived pollutants from different regions and sectors.
Brian Arbic is an Associate Professor in the Department of Earth and Environmental Sciences, with an appointment in the Department of Climate and Space Sciences Engineering and affiliations with Applied and Interdisciplinary Mathematics, Applied Physics, and the Center for the Study of Complex Systems. Arbic is a physical oceanographer primarily interested in the dynamics and energy budgets of oceanic mesoscale eddies (the oceanic equivalent of atmospheric weather systems), the large-scale oceanic general circulation, and tides. He has also studied paleotides, tsunamis, and the decadal variability of subsurface ocean temperatures and salinities. His primary tools are numerical models of the ocean. Arbic uses both realistic models, such as the HYbrid Coordinate Ocean Model (HYCOM) being used as a U.S. Navy ocean forecast model, and idealized models. He frequently compares the outputs of such models to oceanic observations, taken with a variety of instruments. Comparison of models and observations helps us to improve models and ideas about how the ocean works. His research has often been interdisciplinary, involving collaborations with scientists outside of my discipline, such as glaciologists, geodynamicists, and marine geophysicists.
Microbial communities host incredible biological diversity that is encoded at the genomic level. The recent application of high-throughput DNA-sequencing technologies to these communities provides exciting new insights into uncultured organisms while presenting new computational challenges associated with massive and multidimensional data. Professor Dick’s laboratory utilizes such metagenomic and metatranscriptomic approaches to problems in environmental and geological science, addressing questions such as: How do microorganisms control elemental cycles in deep-sea hydrothermal systems? How did microbial processes influence the timing of Earth’s oxygenation? Computational applications focus on metagenomic and metatranscriptomic assembly, comparative genomics, and “binning,” whereby fragmentary metagenomic sequences of unknown origin are assigned to organisms on the basis of genome signatures of nucleotide composition.