Geospatial Scientist with Security Clearance

Employer
Oak Ridge National Laboratory
Location
Oak Ridge, Tennessee
Posted
Apr 01, 2024
Closes
Apr 17, 2024
Ref
2739085934
Discipline
Safety / Security
Position Type
Scientist
Specialty
Other
Hours
Full Time
Organization Type
Corporate
Requisition Id 12735 Overview: As a U.S. Department of Energy (DOE) Office of Science national laboratory, Oak Ridge National Laboratory (ORNL) has an extraordinary 80-year history of solving the nation's biggest problems. We have a dedicated and creative staff of over 6,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL's broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation. We are seeking expertise in geospatial data science to support population research projects at ORNL. This position resides in the Human Geography (HG) Group in the Human Dynamics Section, Geospatial Science and Human Security (GSHS) Division, National Security Sciences Directorate, at Oak Ridge National Laboratory (ORNL). As part of our team, your research will support Federally-funded national security missions by developing the next generation of population models. The Human Geography Geospatial Data Scientist performs research to improve techniques used to produce high-fidelity population models that account for the complex connections between humans and their physical, cultural, and socioeconomic landscapes. This position also develops new methodologies that overcome the data challenges in known areas of the world to better estimate current and predict future population distributions. Other opportunities may include crosscutting division and lab initiatives, working on multidisciplinary projects to address equity, health, and energy challenges through the development of novel algorithms and population distribution datasets. The HG Group at ORNL leads the development of methodologies, tools, and capabilities to advance knowledge of population distribution, geodemographics, and population futures. Leveraging capabilities across the GSHS Division and ORNL, HG staff lead interdisciplinary projects to enhance the spatio-temporal resolution of population estimates with respect to the built environment and human activity spaces. Major Duties/Responsibilities: Develop new and existing population and geodemographic models through statistical or computational methods for improvements to high-resolution gridded population datasets.
Analyze and validate population distribution datasets and improve reporting of confidence or uncertainty in the resulting population distribution or density datasets.
Contribute to journal publications; participate in conferences; and engage with other scientists, technicians, and analysts in the private sector, academia, and US Government communities.
Deliver strong science and technology artifacts demonstrating research innovation for our sponsors. All team members deliver ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace - in how we treat one another, work together, and measure success. Basic Qualifications: Requires a PhD in geography, data science, computer science, or a related field.
Experience in manipulating large scale physical geospatial data including administrative boundaries, census statistics, land use/land cover data, Earth Observation, and infrastructure data. Experience developing land-use/land cover and infrastructure projection models for population forecasting.
Experience in geospatial analysis including use of open source and/or commercial geospatial tools such as ArcGIS, QGIS, or PostGIS.
Experience with Python, R, and/or other similar languages for statistical analysis.
Demonstrated record of research as evidenced by scientific output including peer-reviewed publications and presentations. Preferred Qualifications: Experience with research or development about different cultures and cultural practices in the U.S. and around the world.
Experience in analyzing and interacting with social media, digital trace data, or time series data.
Experience with remote sensing and image interpretation including multispectral and hyperspectral data, spectral analysis, and LiDAR.
Experience leading research initiatives with colleagues or team members. Capable of working successfully in a team environment. Special Requirements: Visa sponsorship is available for this position. HSPD-12 PIV badge: This position requires the ability to obtain and maintain an HSPD-12 PIV badge. Benefits at ORNL: ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience. Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts. If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: or call 1 In addition, we offer a flexible work environment that supports both the organization and the employee. A hybrid/onsite working arrangement may be available with this position. This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired. We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment. If you have trouble applying for a position, please email . ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.