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R&D Scientist

Date: May 9, 2022

Location: Oak Ridge, TN, US, 37830

Company: Oak Ridge National Laboratory

Requisition Id 8219 

Position Overview

The Geospatial Science and Human Security Division (GSHSD) seeks multiple R&D Scientists within the Location Intelligence group. This position is within the Division’s Human Dynamics section and part of the National Security Science Directorate. The Location Intelligence Group performs ground-breaking research into place-based knowledge extraction, human mobility modeling, spatial data, and geosocial discovery. Leveraging primarily “non-traditional” geospatial data sources such as volunteered geographic information (VGI), internet of things (IoT) data, and telemetered sensor sources, and harmonizing with commercial and open data sources, the Location Intelligence group delivers novel approaches and technologies for describing places, points of interest, events, activities, land use, populations, as well as the patterns of life among them. The group’s dynamic content portfolio addresses the timely need to broaden research in network spatialization, activity-based analysis, transformation, human mobility modeling, semantic web ontology, temporal dynamics to describe the landscape and patterns of activity within it, using novel and non-traditional techniques.


The research in human mobility modeling has been continuously evolving for the past two decades, with an initial emphasis on developing theoretical models such as random walk and Levy flight. Recently, with the widespread availability of telemetric data (e.g., GPS footprints, mac traps, network logs), there is an unparalleled opportunity to model data-driven human mobility patterns at very fine scales in both space and time.  Accurate modeling of human mobility has applications in many areas such as epidemiology, urban planning, disaster recovery, humanitarian missions, network protocol optimization, and the various aspects of national security. The precision and accuracy of human mobility modeling rely heavily on the availability of high-quality input data layers such as population, land use, temporal dynamics, and points of interest, among others. Human mobility modeling has two aspects – understanding and characterizing real-world mobility patterns of specific populations and places and using that understanding to develop models to generate synthetic representations of real-world mobility.  This position seeks early career researchers to drive the innovation and transformative impact in the science of both these areas to support the establishment and growth of a human mobility R&D portfolio. Researchers are expected to innovate and invent new scientific methodologies for human mobility in these areas and beyond through research in human behavior, multi-scale land-use modeling, trajectory analysis, agent-based simulations, spatially explicit and geography-cognizant artificial intelligence, routing, conflating social-physical spaces, geographic information retrieval, and semantic web, among others.


Our commitment to diversity:  

As we strive to become the world’s premier research institution in the sciences and technologies that underpin critical national security missions, we are committed to creating an inclusive environment that highly values a diverse workforce.  We recognize that breadth of perspectives, insights, and experiences is necessary to drive innovation and discovery mission-critical to national security sciences.  Our commitment extends beyond our workforce to the next generation of researchers with STEM education outreach that seeks to engage a diverse range of students.


Major Duties and Responsibilities:

  • Develop novel capabilities and competencies in human mobility modeling research and development.
  • Develop approaches to generate population-scale agent-based microsimulations at very fine space-time resolution.
  • Develop and prototype human mobility platforms for accelerated and scalable analysis.
  • Develop qualitative and quantitative methodologies in understanding and characterizing human mobility patterns.
  • Develop novel methods for data conflation, dynamic change detection, automatic attribution, artificial intelligence-driven research, and development.  
  • Detection and analysis of trajectory data noise and anomalies.
  • Support development of platforms for spatialization, visualization, and analysis of human mobility information.
  • Lead and support publications of scientific artifacts (publications, patents, invention disclosures, software applications, and software repositories) to share innovative research with the science community.
  • Regularly organize and attend conferences, participate in panels, broaden industry and academic engagements.
  • Development of approaches pertinent to geosocial sensing and urban dynamics application.


Basic Requirements

  • Ph.D. in computer science, engineering, GIScience, geography, social sciences, or related fields.
  • Experience performing research in relevant fields such as network science, spatial data mining, geosocial analytics, spatial knowledge graphs, computational social science, geography, or related fields.
  • Proficiency in agent-based microsimulation, trajectory data analysis, data visualization, and data analysis
  • Experience working with open-source or commercial geospatial tools such as PostgreSQL, PostGIS, QGIS, and ArcGIS to build, curate, and manage large-scale spatial databases.
  • Experience developing, deploying, and using cloud-native capabilities and services.
  • Experience with C/C++, Java, Python, R, and other similar languages for data manipulation, exploration, graph analysis, and statistical analysis.
  • Excellent written and verbal communication and demonstrated ability to work in interdisciplinary teams.


Preferred Qualifications:

  • Experience characterizing human mobility patterns and developing human mobility models that provide baseline value to the sponsored R&D.
  • Experience developing computational methods to exploit large structured and unstructured open-source datasets for modeling purposes.
  • Experience developing large-scale micro simulations and deploying them on high-performance computing architecture.
  • Experience with digital trace data in exploring and developing intent-driven learning models based on socio-physical interactions.
  • Experience working with version control systems such as Git.
  • Experience with database technologies such as MySQL and ElasticSearch to store, analyze, and manipulate data.
  • Experience in statistics, socioeconomics, computational social sciences, activity and event data, GPS footprint, mac traps, and working with social media data.


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.

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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.

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