【简介】博士后招聘网整理分享“美国蒙大拿州立大学2022年招聘博士后职位（地理空间和机器学习）”，浏览查询更多博士后招聘计划请访问博士后招聘网。

美国蒙大拿州立大学2022年招聘博士后职位（地理空间和机器学习）

Postdoctoral Researcher

Montana State University

Description

Position Details

The Department of Earth Sciences at Montana State University (MSU) seeks a postdoctoral researcher to work with incoming-faculty Cascade Tuholske, Asst. Prof. of Human-Environment Geography. Beginning in fall 2022, the appointment will be for two years conditional on performance the first year. The postdoctoral researcher will lead research as part of a NASA-funded project to assess the relationship between maternal/child health, extreme heat and land- cover/land change (LCLUC) in sub-Saharan Africa and a Microsoft-funded project to map high-resolution changes in risk to extreme heat and flooding worldwide.

Concurrently, the postdoctoral researcher will contribute to the newly founded Geospatial Core Facility (GCF) at MSU. The overarching goal of the GCF is to expand and facilitate interdisciplinary geospatial research, teaching, and external funding across campus. Through the GCF, the postdoctoral researcher will have the opportunity to develop independent research streams related to the postdoc's interests and to collaborate with GCF's highly interdisciplinary team.

The successful applicant will have deep expertise in remote sensing of LCLUC, a commitment to the advancement of diversity, equity and inclusion in science, a demonstrated publication track record, and be a curious and thoughtful scholar. Further, the successful applicant will have strong technical expertise in geospatial and machine learning software development in Python and domain expertise in integrating LCLUC analysis with socioeconomic data to understand socioecological systems in low- and middle-income countries.

Duties and Responsibilities

Responsible for leading collaborative research on maternal/child health, extreme heat and land-cover/land change (LCLUC) in sub-Saharan Africa that produces peer-reviewed scientific publications.

Responsible for developing LCLUC python-based tools and datasets for Microsoft-funded grant to assess changes in risk to extreme heat and flooding worldwide, as well as author peer-reviewed scientific publications.

Responsible for supporting the mission of the Geospatial Core Facility (GCF) by developing independent research streams focused on advancing remote sensing and geo-spatial sciences

Attend and present at conferences and workshops

Required Qualifications – Experience, Education, Knowledge & Skills

PhD in Geography, Geographic Information Sciences, Earth Sciences, Computer Science, or related field.

Demonstrated strong expertise applying remote sensing and geospatial analysis to assess LCLUC to support inter-disciplinary research.

Experience developing machine learning (ML) models to identify LCLUC with remote-sensed imagery.

Effective oral and written communication, including data visualization (maps, infographics, figures, etc.).

Strong expertise in Python and Github.

Demonstrated ability in research/project management while working independently and as part of a team.

Experience with fundamentals of Unix shell command line scripting.

Experience with processing large, remote-sensed, climate, and meteorological datasets (parallel processing, cluster computing, etc.).

Preferred Qualifications – Experience, Education, Knowledge & Skills

Research experience in public health or social science discipline.

Expertise in land-atmosphere coupling.

Experience using global circulation model (GCM) output data.

Expertise with spatial statistics.

Experience in web-based applications of geospatial data.

Experience with parallel computing and/or high-performance computing.

Mastery of Unix shell command line scripting.

Experience with cloud-based geo-spatial data environments (Google Earth Engine, Azure Planetary Computer, AWS, etc.)

Experience in teaching, or willingness to co-teach geospatial workshops.

The Successful Candidate Will

Proven track record publishing peer-review manuscripts.

Demonstrate Python expertise that includes using machine learning to assess remote-sensed imagery to track LCLUC processes.

Demonstrate understanding of Github and Unix shell.

Exhibit initiative to work both independently and collaboratively, as wells thoughtful and creative scholarship.

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