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Research Engineer/Scientist I - Environmental Remote Sensing Michigan Tech Research Institute (Ann Arbor, MI)
The Research Scientist I – Remote Sensing position provides support for MTRI programs focused on the development and application of remote sensing and geospatial analysis to solve governmental and societal needs through sponsored research. Knowledge of remote sensing theory and an understanding of remote sensing applications for environmental and/or Earth science research is required. The applicant should be familiar with one or more of the following remote sensing modalities of interest: active and passive systems, microwave (SAR), multi-spectral, hyperspectral, and infrared sensing (IR). The applicant will be expected to help develop proposals for remote sensing research projects that apply their knowledge of sensing and image processing to research questions. The applicant will also be expected to conduct fieldwork in remote environments. Examples of current research areas the Remote Sensing Scientist may support include wildland and prescribed fire mapping and effects assessment, Great Lakes aquatic sensing, invasive species mapping, wetlands assessment, wildland fire danger and emissions mapping, processing, and analysis of remote sensing data through custom coding and analysis, and improved geotemporal visualization of complex data and patterns. This in an in-person position based at MTRI in Ann Arbor, MI (https://mtu.edu/mtri).
Research Scientist I – Applied Mathematician/Statistician Michigan Tech Research Institute (Ann Arbor, MI)
MTRI (www.mtu.edu/mtri) is seeking highly motivated, intellectually curious, professional statisticians, mathematicians, and engineers interested in developing new tools and applications of statistical signal processing, sequential planning, and optimization. Specifically, this position involves supporting customer-driven research needs from both government and commercial sponsors. The role involves collaboration with senior engineers and scientists to research, design, and evaluate new cutting-edge tools for application to remote sensing. A successful candidate will have a solid background in pure and applied mathematics and/or statistics and a desire to apply theory from these fields to a broad range of remote sensing and sensor modalities. In addition, an ideal candidate would have prior experience writing scientific software to investigate the efficacy of the proposed techniques.