Postdoctoral Research Associate - AI/ML for Land Cover Forecasting and Risk Evaluation

Location

Oak Ridge, TN | United States

Job description

Requisition Id 12443 

Overview:

As a U.S. Department of Energy (DOE) Office of Science 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.

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 seeking a Postdoctoral Research Associate who will support the GeoAI Research Group within the Geospatial Science and Human Security Division at Oak Ridge National Laboratory (ORNL) to leverage modern concepts of Generative AI and physics-based machine learning for land cover forecasting. Intended use of these capabilities include urban planning, hydrological modeling, and wildfire risk mitigation strategies. In addition to model development, research activities include the design of uncertainty estimation mechanisms and evaluation protocols that capture domain knowledge and application requirements.

Within the GeoAI group, you will have the opportunity to develop and publish on novel solutions to national and global problems using cutting edge physics-based machine learning, generative artificial intelligence, spatial and spatiotemporal methods. You will be able define and grow your scientific brand at ORNL through your success in projects, laboratory presentations and networks, and through the cross-directorate interdisciplinary teaming. You will also have an opportunity to grow your career with high external visibility by attending, presenting, and networking at peer reviewed conferences.

Major Duties/Responsibilities:

• Contribute to the conceptualization and design of new data-driven algorithms for forecasting future scenarios of land-use from historical data and auxiliary geospatial data sources.
• Provide coding support to implement diffusion-based generative deep learning models conditioned on heterogenous geospatial data modalities including historical land-cover data, population density maps, terrain maps, as well as local climate zones and critical infrastructure data.
• Support the design of physics-based machine learning and uncertainty estimation mechanisms and evaluation protocols that ensure forecasts are constrained by urban theories and usable for downstream applications such as urban planning, hydrological modeling, and risk mitigation strategies.
• Participate in the development of proposals for research projects.
• Publish research results in journal articles, conference papers, and technical manuals.
• Lead by example to ensure all work is carried out safely, securely, and in compliance with ORNL policies, standards, and procedures.
• Exemplify a commitment to excellence in research, operations, and community engagement, and work cooperatively to leverage scientific capabilities across ORNL.
• Work in a highly collaborative environment with data scientists, machine learning scientists, remote sensing scientists, HPC engineers, earth and planetary scientists, and geographers to deliver research and development prototypes. 
• 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.

This position reports to a Group Leader and works closely with R&D Section Heads to implement the group’s scientific vision; develop group members to enable their career advancement; establish capabilities that enable programs to excel at the forefront of science and technology; perform R&D to advance the field of knowledge and/or technology in one’s respective specialty; sets, implements, and models standards for performance of work consistent with Environment, Safety, Security, Health, and Quality (ESH&Q) requirements and business rules; and ensures a diverse and inclusive work environment where every employee feels safe, heard, and appreciated—a workplace that sets an example for the broader community.

The National Security Sciences Directorate conducts research and development to confront some of the nation’s most difficult security challenges and adversaries. Our directorate houses S&T leadership in cybersecurity and cyber-physical resiliency, data analytics, geospatial science and technology, nuclear nonproliferation, and high-performance computing for sensitive national security missions. We draw on the Laboratory’s exceptional facilities and work closely with leading researchers in other areas at the lab such as nuclear and chemical sciences and engineering, applied materials, advanced manufacturing, biosecurity, transportation, and computing. Our multi-disciplinary research teams are passionate about discovery and innovation as we create science-based solutions to complex security threats that put public safety, national defense, energy infrastructure, and the economy at risk.

Basic Qualifications:

• A PhD in electrical and computer engineering, earth and planetary sciences, atmospheric science, or a related field completed within the last 5 years
• Experience in developing AI/ML methods for analyzing large-scale Earth observation and simulated datasets
• Strong research profile and be able to conduct independent research
• Strong written and oral communication skills
• The ability to work in a dynamic, team environment

Preferred Qualifications:

• Experience working with spatial-temporal datasets, remote sensing imagery, simulations, and time series analysis
• Experience in the development, evaluation of climate and Earth system models
• Hands-on experience with training machine learning models on high performance computing infrastructures leveraging GPU accelerators
• Building frameworks for predictive understanding of land forecasting models with a particular interest in generative modeling
• Knowledge of land surface processes and land-climate feedbacks
• 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

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to [email protected] with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

• Login to your account via jobs.ornl.gov
• View Profile
• Under the My Documents section, select Add a Document

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: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Life Insurance, Pet Insurance, 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: [email protected] .

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 [email protected].

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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