Climate Change, Forest Carbon and Geospatial MRV Research Assistant I

Hiring Organization: Department of Forestry
Employment type: Full-Time
Application Due Date: March 2, 2024

Position description

The Department of Forestry at Michigan State University invites applications for a full-time, Climate Change, Forest Carbon and Geospatial MRV Research Assistant who will provide geospatial technical and analytical support to measurement, reporting, and verification (MRV) of forest carbon, in a research environment focused on climate change mitigation in tree-based systems; and deploy models using remote sensing data and machine learning algorithms to map tree carbon in Africa and Asia. This is an end-dated, grant-funded, benefits-eligible, union position, with funding for one year from date of hire, with extension possible depending on continued funding availability.

Duties

The successful candidate will assist in geospatial and remote sensing analysis; measurement, reporting and verification tools development; and software tool development. Specifically, the research assistant performs professional and technical duties within defined parameters involving analysis, development, preparation, implementation and maintenance of geospatial dataset and computer programs; coordinates and performs research and geospatial laboratory operations and analysis; supports field work and operations to meet goals of research projects; supports the development of machine learning models that use UNet machine learning code and models to analyze images for trees as objects; works in a team environment and leads lower-level support and student staff on assigned projects of limited scope and complexity or on small components of larger projects; consults with key stakeholders to perform needs assessments, which are then converted into computer programs that satisfy those needs while conforming to prescribed designs and specifications. The research assistant integrates geospatial information systems, such as databases, GIS and remote sensing (satellite) imagery with online information systems in a Web browser; supports back- and front-end development of cloud-based, Web-enabled applications in support of an international research project on climate change and forests; and supports developing machine learning tools and models to analyze satellite imagery. The research assistant also assists in the design and implementation of computer software models, data handling systems and tools development using applicable computer programming languages, scripts and IDEs; builds database-backed Web applications as well as machine learning; and will use UNet Convolutional Neural Networks, Jupyter Notebooks, R, Python, Django, Windows Web-server environments and relational databases.

Global Observatory for Ecosystem Services

The GOES team uses interdisciplinary methods to understand the role of forest and ecosystem change at the global scale. We work in tropical systems in forests, woodlands and trees outside of forests. Our work is nested in actionable science to support climate change policy frameworks and the intersection of environment and development. Our research and observing systems are applied to climate change mitigation and reducing greenhouse gas emissions. The aim is to provide knowledge and technical capacity building for low carbon management in the forestry and agriculture sectors. We have projects around the world, working with international partners to conserve forests and mitigate climate change through new models of low carbon sustainable forest management. We emphasize models for reducing deforestation and forest degradation, and forest landscape restoration. Find out more at our web site at www.goeslab.us

Minimum Requirements

The job requires: knowledge equivalent to that which normally would be acquired by completing a four-year college degree program in forestry measurements, quantitative forestry, geospatial information systems, computer science, data science or other related STEM fields; one to three years of related and progressively more responsible or expansive work experience in standard laboratory procedures and safety requirements and performing analytical and research techniques in machine learning models; experience with the following software: UNet Convolutional Neural Networks, Jupyter Notebooks, R, Python, Django, Windows Web-server environments, and relational databases; or an equivalent combination of education and experience.

Preferred Qualifications

Ability to perform technical system analysis and to write and maintain effective Web-based mapping programs and spatial models in an independent, entrepreneurial, focused, and self-driven manner. The candidate would be expected to write well, have good presentation and communication skills and work well in an extensive globally distributed team representing diverse cross-cultural backgrounds. Technical abilities in remote sensing, GIS, field measurements of tree and forest carbon, MRV systems, and machine learning are desired.

Location

The position is based at Michigan State University in East Lansing, MI, USA. MSU strives to provide a flexible work environment and this position has been designated as remote-friendly, which means some or all of the duties can be performed remotely as mutually agreed upon. Formally established in 1902, Michigan State’s Department of Forestry was among the first undergraduate forestry programs in the U.S. and is accredited by the Society of American Foresters. The Department is a vibrant, growing, internationally recognized unit committed to interdisciplinary education, research, and extension to understand and resolve environmental and natural resource issues.

To Apply

For consideration, submit your application online at http://careers.msu.edu to position number 931431. Upload the following required documents: a) letter of interest that details your qualifications for the position; b) current resume/curriculum vitae; and c) contact information for three professional references. Incomplete applications will not be considered.

Application deadline

The search committee will begin reviewing applications on March 6, 2024, and continue until a suitable candidate is selected. Questions regarding this position can be addressed to the Search Committee Chair: Dr. David Skole, Department of Forestry, Michigan State University, East Lansing, MI 48824, USA, email: skole@msu.edu.

MSU is an affirmative action, equal opportunity employer, committed to achieving excellence through a diverse workforce and an inclusive culture that encourages all people to reach their full potential. We actively encourage applications from, and nominations of, women, persons of color, veterans, persons with disabilities and other individuals who can contribute to the intellectual diversity and cultural richness at Michigan State University. MSU is committed to providing a work environment that supports employees’ work and personal life.

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