Research Scientist Numerical Terradynamic Simulation Group

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The
Numerical Terradynamic Simulation Group
(NTSG) invites applications for a
Research Scientist
to join an interdisciplinary group pioneering conservation science in rangelands of North America. We seek candidates with exceptional geospatial analytics, machine learning, and cloud computing skills to assist with ongoing science that drives conservation implementation across millions of acres in the western United States. This position is a full-time appointment with two years of funding contingent on performance.
The research scientist will contribute to ongoing research funded by USDA’s Agricultural Research Service (ARS) and Natural Resources Conservation Service (NRCS), the Bureau of Land Management (BLM), and other partners on ways to enhance the conservation and resilience of North American rangelands on private and public lands.
The successful candidate must be highly independent and collaborative with UM scientists and affiliates. Work assignments will be a combination of short (less than two weeks) and moderate (up to 6 months) duration tasks; the appointed individual will be expected to manage multiple tasks simultaneously and prioritize work based on project needs and input from senior research scientists. The selected individual will be able to see intellectually and technically complex analyses to their conclusion, which may involve developing methodological approaches and reviewing, analyzing, and interpreting scientific data and results from the project.
The primary duties of the appointee are to perform computational analysis of large datasets (satellite records, ecological time-series data) and to update computer-based models of environmental importance to conservation partners. Day-to-day responsibilities include using Google Earth Engine, cloud-based HPC and storage services, and advanced statistical tools in R or Python to shape and analyze data. Secondary duties include participating in research group meetings that may consist of oral and written brief reports with federal and NGO partners, preparing and packaging data for public presentations, and assisting with manuscript preparation.
Questions about the position may be directed to Dr. Scott Morford ( ****
**MEMBERS ONLY**SIGN UP NOW***. is an Affirmative Action/Equal Opportunity employer and has a strong institutional commitment to the principle of diversity in all areas. In that spirit, we are particularly interested in receiving applications from a broad spectrum of qualified people who would assist the University in demonstrating its five priorities for action
: Place student success at the center of all we do; drive excellence and innovation in teaching, learning, and research; embody the principle of “mission first, people always; partner with place; and proudly tell the UM story.
Position Details
Position is full-time, 1.0 FTE, Letter of Appointment and includes a comprehensive and competitive benefits
Benefits package includes Insurance, mandatory retirement plan, partial tuition waiver, and wellness program
Salary for this position is $65,000 - $80,000 per year commensurate with qualifications
Minimum Required Experience
M.S. or Ph.D. in systems ecology, remote sensing, natural resource management, earth sciences, or a similar field
Experience processing large, remotely sensed datasets using ML tools and publishing results
Experience in applied environmental science, land management, or wildlife conservation
Demonstrated experience in advanced research capabilities required to carry out innovative and insightful research using remote sensing and machine learning on issues related to continental-scale conservation
Experience identifying, analyzing, and summarizing relevant literature in environmental science, applied statistics, and machine learning
Advanced computational skills using Google Earth Engine or other HPC-enabled remote sensing platforms
Advanced skills in statistical analysis using tools in Python or R
Applied experience using standard ML packages for training and inference of convolutional neural networks (e.g., TensorFlow or PyTorch)
Familiarity with Unix, shell scripting, and GDAL
Ability to use GIS to build presentation-quality maps
Preferred Qualifications
Genuine interest in applied science that supports private land conservation
About NTSG and UM
The Numerical Terradynamic Simulation Group (NTSG) is a research laboratory at **MEMBERS ONLY**SIGN UP NOW***. in Missoula pioneering new approaches for landscape ecological and hydrological analyses. The primary focus of NTSG is to understand how terrestrial vegetation responds to climate variability and influences energy, water, and carbon cycles. NTSG conducts research over a broad range of spatial scales from individual landscape units to basin, continental and global domains. NTSG strongly emphasizes applying ecological theory and environmental analysis using computational process modeling, satellite remote sensing, and GIS. NTSG is a NASA Earth Science Information Partner (ESIP) and is involved with the NASA Earth Observing System as a repository for various global land data products.
To learn more about **MEMBERS ONLY**SIGN UP NOW***., Missoula, and the State of Montana, please visit the links below.
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University Highlights
Criminal Background Investigation is required prior to the Offer of Employment In accordance with University regulations, finalists for this position will be subject to criminal background investigations. ADA/EOE/AA/Veteran's Preference
Reasonable accommodations are provided in the hiring process for persons with disabilities. For example, this material is available in alternative format upon request. As an Equal Opportunity/Affirmative Action employer, we encourage applications from minorities, veterans, and women. Qualified candidates may request veterans’ or disabilities preference in accordance with state law. References:
References not listed on the application materials may be contacted; notice may be provided to the applicant. Testing:
Individual hiring departments at UM may elect to administer pre-employment tests, which are relevant to essential job functions. Employment Eligibility:
All New Employees must be eligible and show employment eligibility verification by the first date of employment at UM, as legally required (e.g., Form I-9).

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