Land System Science Lead - Assistant Research Professor
Job Description
Position Number:
119042Title:
Assistant Research ProfessorFunctional Title:
Land System Science Lead - Assistant Research ProfessorCategory Status:
15-Fac.Non-Tenured,Continuing ConApplicant Search Category:
FacultyUniversity Authorized FTE:
50Unit:
BSOS-GeographyCampus/College Information:
Founded in 1856, University of Maryland, College Park is the state’s flagship institution. Our 1,250-acre College Park campus is just minutes away from Washington, D.C., and the nexus of the nation’s legislative, executive, and judicial centers of power. This unique proximity to business and technology leaders, federal departments and agencies, and a myriad of research entities, embassies, think tanks, cultural centers, and non-profit organizations is simply unparalleled. Synergistic opportunities for our faculty and students abound and are virtually limitless in the nation’s capital and surrounding areas. The University is committed to attracting and retaining outstanding and diverse faculty and staff that will enhance our stature of preeminence in our three missions of teaching, scholarship, and full engagement in our community, the state of Maryland, and in the world.
Background Checks
Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify you from employment.
Position Summary/Purpose of Position:
The Global Land Programme (GLP) (www.glp.earth), seeks a highly organized and motivated individual to join the Global Land Programme’s International Programme Office (GLP-IPO) as Land System Science Lead at the Assistant Research Professor/Postdoctoral Associate level depending on experience.
The GLP-IPO is hosted by the Department of Geographical Sciences at University of Maryland, College Park. The GLP is a global research network of more than 2300 scientists worldwide supporting the next generation of science-based solutions to land system challenges at local-to-global scales, and delivering knowledge in support of sustainable development. The GLP-IPO, based at UMD, serves as a catalyst to achieve the mission of this international network to enable research for sustainable development of land systems via four main objectives: 1) Setting agendas and facilitating synthesis in land system science; 2) Enabling the production of cutting-edge land system science worldwide; 3) Informing science-based policy on land; and 4) Building capacity of the Land System Science (LSS) community to deliver inclusive, solutions-oriented science.
This new position will support the GLP’s IPO and Scientific Steering Committee (SSC) on a range of analytical and programming activities to investigate the implications of competing claims on land (e.g., nationally determined contributions to reduce GHG emissions, achieving carbon neutrality, conserving biodiversity). These activities will include identifying, cataloging, and wrangling diverse global datasets; synthesizing available data sources to produce analytical generalizations of thematic land system challenges; and overseeing the production and communication of reports, papers, and related high-impact products targeted to diverse policy audiences (e.g., ‘State of the Land’ assessment). The LSS lead will work in consultation with the SSC and analysts drawn from the wider GLP network.
This position is a Professional Track Research Faculty Member (non-tenure position) at either the Post-Doctoral Associate rank or the Assistant Research Professor rank, commensurate with qualifications and experience. Post-Doctoral Associates have limited prior research experience and are within five years of their doctoral degree. Assistant Research Professors conduct independent research and scholarly output. This is a 12-month, 50% effort part-time position. The initial appointment is for three years, renewable. This position offers excellent benefits, including but not limited to health insurance, generous leave package from the first year, retirement subsidy (ORP/Pension System), tuition remission, and many professional development opportunities. This position is also hybrid telework-eligible with flexible work hours. GEOG promotes growth in individuals and a healthy work-life balance within a collaborative culture. The anticipated start date is Fall 2023. The researcher will be located at the University of Maryland with options for telework. There may also be periods of travel, both domestic and foreign, in support of GLP events and projects.
Benefits Summary
Top Benefits and Perks:Minimum Qualifications:
Experience:
An earned doctoral degree in Geographical Sciences or allied fields in environmental sciences, integrative geography (social and natural science) is required. Candidates with doctoral degrees in other fields (for example, Physics, Computer Science, and Electrical Engineering) with a demonstrated knowledge and understanding of research topics and methods of LSS will also be considered.
Knowledge, Skills, and Abilities:
An earned doctoral degree in Geographical Sciences or allied fields in environmental sciences, integrative geography (social and natural science) is required. Candidates with doctoral degrees in other fields (for example, Physics, Computer Science, and Electrical Engineering) with a demonstrated knowledge and understanding of research topics and methods of LSS will also be considered.
Knowledge, Skills, and Abilities:
- Competent programming and statistical skills (e.g., such as Python, IDL, MatLab, C/C++, R, TensorFlow) are required.
- Candidates at the level of Assistant Research Professor must have a demonstrated ability to independently conduct research as evidenced by peer-reviewed publications.
Preferences:
- Experience with science communication, geovisualization, and/or mixed-methods or other synthesis methods is desired.
- A background in LSS, or related research areas (e.g., social-ecological systems, coupled human-natural systems), broadly construed.
- Excellent quantitative and analytical skills, and prior experience analyzing large-scale geospatial and mixed-mode data.
- Ability to compile, clean, wrangle, visualize, and manage large amounts of tabular and geospatial data; GIS.
- A solid foundation in applied statistics (i.e. regression analysis); and some basic familiarity with synthesis and/or mixed-methods research approaches.
- Strong communication (spoken and written) and interpersonal skills.
- The ability to work independently, as well as with a close-knit IPO team and the broader international LSS community.
Additional Information:
Applications should include a personal statement of background and experience relevant to the position, a signed, dated Curriculum Vitae, reprints (or accessible download urls) of selected peer-reviewed publications, and names and addresses (including e-mail) of 3-5 references. Applicants with specific research interests they would like to pursue at UMD are encouraged to contact (adebrem@umd.edu) to discuss their potential plans.
For best consideration applications should be submitted no later than August 14, 2023, but the search will continue until a suitable candidate is appointed.
Applications from women and minorities are particularly sought. The University of Maryland is an Equal Opportunity Affirmative Action Employer.
Further information on the Global Land Programme and the research programs of the Department may be obtained from the address above and can be found at https://www.glp.earth/ and http://www.geog.umd.edu.
Posting Date:
07/07/2023Open Until Filled
YesBest Consideration Date
08/14/2023Diversity Statement:
The University of Maryland, College Park, an equal opportunity/affirmative action employer, complies with all applicable federal and state laws and regulations regarding nondiscrimination and affirmative action; all qualified applicants will receive consideration for employment. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, religion, sex, national origin, physical or mental disability, protected veteran status, age, gender identity or expression, sexual orientation, creed, marital status, political affiliation, personal appearance, or on the basis of rights secured by the First Amendment, in all aspects of employment, educational programs and activities, and admissions.
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