Postdoctoral Research Associate - Urban System Visualization, Integration & Optimization
Date: Oct 23, 2024
Location: Oak Ridge, TN, US, 37830
Company: Oak Ridge National Laboratory
Requisition Id 13620
Overview:
The Grid Interactive Controls (GIC) Group in the Electrification and Energy Infrastructure Division (EEID) within the Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate. The Grid Interactive Controls group specializes in pioneering innovations at the edge of today’s power grid, concentrating on fortifying grid security, enhancing reliability, bolstering resilience and advancing decarbonization. Our primary focus lies in the comprehensive 'Everything-to-Grid' (X2G) strategies, developing cutting-edge solutions in grid-edge integration and control. Our commitment revolves around seamlessly incorporating emerging distributed energy resources, including demand response emerging at the grid edge, providing essential services crucial to its reliable operation. Employing a diverse range of disciplines such as urban modeling, control theory, optimization, economics, game theory, data analytics, and machine learning, the GIC Group delves deeply into understanding intricate grid-edge interactions and operations. Researchers are dedicated to laying the groundwork for optimal X2G integration and utilization. Group initiatives encompass advanced urban system modeling, analysis & visualization, low-cost wireless sensing technologies, and interoperable & scalable control mechanisms tailored for the grid edge. Research promotes grid-interactive efficient buildings as a pivotal component in advancing building-to-grid integration, amplifying their role in electrification of heating and ultimately shaping the future decarbonized grid.
Specifically, the urban energy modeling team within the GIC Group has created and simulated a model of every U.S. building. This involves urban-scale building energy modeling at the resolution of individual buildings and at the scale of nations to analyze building codes, energy efficiency, demand response, and climate change impacts toward a sustainable and resilient built environment. These activities involve multi-disciplinary collaboration across ORNL, collaborative partnerships and NDAs with over 20 well-known companies, and significant awards on world-class computational resources. This team achieved world-first simulation of 125.7 million U.S. buildings, public release of 122.9 million building energy models (bit.ly/ModelAmerica), and has scaled EnergyPlus to over 1 million simulations per hour on supercomputers. In partnership with major organizations, the team is actively improving the data and algorithms of the Automatic Building Energy Modeling (AutoBEM, bit.ly/AutoBEM) software suite which involves big data processing, data analytics, machine learning, high-performance computing resources, computer vision, and building science to create, model, simulate, validate, and analyze building performance to create software prototypes (e.g. dashboards, bit.ly/virtual_epb) for actionable use of building data, models, or analysis by specific stakeholders. Over 50 million core-hours have been awarded to release a Model America v2.0 dataset in 2022.
Selection will be based on qualifications, relevant experience, skills, and education. The successful candidate should be highly self-motivated and independent in conducting research under general guidance, and is expected to prepare manuscripts for scientific publication and present the work to sponsors and at conferences. This position requires development of innovative software techniques, knowledge of building energy modeling, multi-sector grid edge technology integration, frequent and consistent review of related literatur. It also requires frequent interactions and collaboration with a multi-disciplinary team of researchers from universities, national laboratories, and private industry for the development of technical capabilities, demonstrations, proposals, oral presentations, and publications.
As part of the urban energy modeling team, the candidate will assist in the development and implementation of data organization and software development for scalable use and analysis of business-sensitive data by supporting senior R&D staff in 1) the invention or improvement of innovative algorithms for detection or estimation of building characteristics, 2) validation against known data sources, 3) scalable generation/simulation of buildings using OpenStudio and EnergyPlus, and/or 4) use of Artificial Intelligence (AI) techniques to quantify and improve city-to-nation scales of individual building energy models. As part of the R&D, the candidate will be required to apply the computational skills to manage big data, create and extend existing software capabilities, and develop user-centered web interfaces; and utilize the system engineering knowledge to ensure seamless integration of data, algorithms, and knowledge into comprehensive solutions.
Major Duties/Responsibilities:
- Proven RDD&D experience in building energy modeling, software development, Machine Learning/Artificial Intelligence (ML/AI), or Optimization and Operations Research.
- Design, implement, and optimize scalable software systems to manage and process large datasets related to building energy modeling and data visualization
- Design and implement algorithms and techniques for integrating multi-system energy technologies, supporting comprehensive simulations and analyses at various scales.
- Experience with OpenStudio measures and EnergyPlus
- Create user interfaces for software applications that facilitate stakeholder interaction with building data and models.
- Excellent communication skills for conveying technical material to both scientists and non-scientists in both written and oral presentations
- Self-disciplined work ethic and eagerness to tackle challenging research problems
- Strong desire to work in a team environment
- 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:
- A PhD in computer science, industrial engineering, electrical and computer engineering, design computation, or a related field completed within the last 5 years.
Preferred Qualifications:
- Development or demonstration of urban-scale building energy modeling/analysis
- Experience with geospatial data visualization tools such as ArcGIS, or similar.
- Experience with network optimization techniques and system engineering applications.
- Experience with PyTorch, Jupyter Notebooks, TensorFlow
- Experience with modern programming languages, and Git version control system
- Familiarity with developing or debugging software for world-class high-performance computing resources
- Demonstration of projects involving big data management (esp. TBs)
- Experience working in Agile/SCRUM teams
- Excellent written and oral communication skills
- Motivated and conscientious self-starter with the ability to work independently, follow-up on all action items, and 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 need
- Some travel will be required for this position.
Special Requirements:
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 up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.
Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to postdocrecruitment@ornl.gov 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 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: ORNLRecruiting@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.
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