Research Associate Scientist in Bayesian Machine Learning for Geospatial Applications

Requisition Id 9943 

Overview: 

The National Security Sciences Directorate at Oak Ridge National Laboratory leads scientific and technological breakthroughs to confront some of the nation’s most difficult security challenges. We develop interdisciplinary applications needed for the security of our nation today and target our vision on how these challenges may manifest themselves in a decade or more. Our research and development focus on cybersecurity and cyber physical resiliency, data analytics, geospatial science and technology, nuclear nonproliferation, and high-performance computing for sensitive national security missions. We also enhance ORNL contributions to national security challenges by working closely with leading researchers at the lab in areas such as nuclear and chemical sciences and engineering, applied materials, advanced manufacturing, biosecurity, transportation, and computing. We are currently seeking a qualified applicant for a research scientist position in Bayesian machine learning within the Geographic Data Science Section and GeoAI group. The position requires strong skills in computer science, mathematics, machine learning, and Bayesian reasoning (e.g., probabilistic graph modeling, hierarchical modeling)  This position creates a unique opportunity to work with a talented, interdisciplinary team of R&D professionals across research groups to build new research directions and have immediate impacts on key national security challenges and questions.

The successful candidate will work on advancing GeoAI methods toward the understanding of human processes as they interact with the virtual, natural, and built environment. We are especially interested in developing highly detailed building attribution data sets, testing new models for how humans occupy buildings, detecting and monitoring change, and continually improving our understanding for how all these impact climate resiliency, energy, water, demography, mobility, and national security. You will have the chance to creatively use interdisciplinary methods from computational statistics, Bayesian reasoning, machine learning, geographical information sciences, and many others topics to help frame and solve the above problems on a national and global scale.

Major Duties/Responsibilities: 

• Lead and contribute to the design, development, and implementation of new models, methods, and algorithms that improve our understanding of human dynamics and the built environment
• Evaluate and improve existing population modeling processes, workflows, and codebases where appropriate.
• Support the design of statistical sampling strategies and accelerating the implementation of such tools.
• Contribute to and lead team publications in journals, participate in conferences, and engage with other scientists and analysts in the private sector, academia, and US Government communities.

Basic Qualifications:

• Ph.D. in computational data sciences, mathematics, geography, statistics, computer engineering or equivalent field with 1-2 years of research
• Knowledge of Bayesian methods particularly network graphs and hierarchical modeling.
• Demonstrated written and oral scientific communication skills including peer-reviewed publications and presentations.
• Demonstrated record of research as evidenced by scientific output including peer-reviewed publications.
• Excellent skills in written and verbal communication, as well as teamwork.
• Experience working collaboratively in version control systems for source code management such as Git/GitLab.
• Experience with Python, R, and/or other similar languages for statistical analysis.
• Experience with Pandas, Numpy, Pytorch, PYMC, STAN, or other similar tools for Bayesian methods and machine learning.
• Experience with database technologies, particularly to store, analyze, and manipulate geospatial data.

Preferred Qualifications:

• Experience with parallel processing on CPU and/or GPU.
• Knowledge of major challenges in modeling and representing the built environment
• Experience leading research initiatives in a team environment.
• Excellent written and oral communication skills
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory 
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs

Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

For more information about our benefits, working here, and living here, visit the “About” tab at jobs.ornl.gov.

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 ORNLRecruiting@ornl.gov.

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.