Postdoctoral Research Associate : Machine Learning for Complex System Prognostics and Diagnostics
Oak Ridge | Permanent | www.tiptopjob.com |
Requisition Id11726
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 Neutron Sciences Directorate (NScD) at Oak Ridge National Laboratory (ORNL) operates the High Flux Isotope Reactor (HFIR), the United States highest flux reactor:based neutron source, and the Spallation Neutron Source (SNS), the worlds most intense pulsed accelerator:based neutron source. Together these facilities operate 30 instruments for neutron scattering research, each year carrying out more than 1,000 experiments in the physical, chemical, materials, biological and medical sciences. HFIR also provides unique facilities for isotope production and neutron irradiation. To learn more about Neutron Sciences at ORNL go to:
neutrons.ornl.gov
• Oak Ridge National Laboratory is also a leader in computational and computer science, with unique strengths in high:performance computing and data analytics with applications to the physical and biological sciences.
We are seeking a postdoctoral research associate who will focus on machine learning, signal processing, and statistical analysis with emphasis on prognostics and applications. This position resides in the Accelerator Science and Technology Section in the Research Accelerator Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL).
As part of our research team, you will work with accelerator and target systems specialists and machine learning experts to develop, integrate, and apply machine learning methods to improve performance of the SNS 1.7 MW accelerator and target systems.
Major Duties/Responsibilities:
• Develop, implement, and apply novel machine:learning (ML) and statistical methods to sensor and component health monitoring with reporting, anomaly detection, and fault isolation of complex dynamic systems.
• Develop and apply both first principles:based and data:driven techniques to solving complex engineering problems.
• Perform data analysis on large, sparse, and noisy data.
• Perform uncertainty quantification and uncertainty propagation analyses.
• Test, validate, monitor, and maintain deployed ML models on field to ensure operational success.
• 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
nuclear, electrical engineering, mechanical, computer engineering, engineering physics, computational science, or a related field completed within the last 5 years
Preferred Qualifications:
• Basic understanding of ML methodologies and their applications to complex engineering systems.
• Experience with open:source machine:learning tools, such as TensorFlow, Keras, PyTorch, and MLflow.
• Experience with applying and deploying state:of:the:art machine:learning methods for solving complex engineering problems, including diagnostics and prognostics of complex engineered systems.
• Experience with sustainable machine:learning ecosystems, maintaining deployed machine:learning models on field, and adapting to evolving system conditions via continual learning app
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 Neutron Sciences Directorate (NScD) at Oak Ridge National Laboratory (ORNL) operates the High Flux Isotope Reactor (HFIR), the United States highest flux reactor:based neutron source, and the Spallation Neutron Source (SNS), the worlds most intense pulsed accelerator:based neutron source. Together these facilities operate 30 instruments for neutron scattering research, each year carrying out more than 1,000 experiments in the physical, chemical, materials, biological and medical sciences. HFIR also provides unique facilities for isotope production and neutron irradiation. To learn more about Neutron Sciences at ORNL go to:
neutrons.ornl.gov
• Oak Ridge National Laboratory is also a leader in computational and computer science, with unique strengths in high:performance computing and data analytics with applications to the physical and biological sciences.
We are seeking a postdoctoral research associate who will focus on machine learning, signal processing, and statistical analysis with emphasis on prognostics and applications. This position resides in the Accelerator Science and Technology Section in the Research Accelerator Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL).
As part of our research team, you will work with accelerator and target systems specialists and machine learning experts to develop, integrate, and apply machine learning methods to improve performance of the SNS 1.7 MW accelerator and target systems.
Major Duties/Responsibilities:
• Develop, implement, and apply novel machine:learning (ML) and statistical methods to sensor and component health monitoring with reporting, anomaly detection, and fault isolation of complex dynamic systems.
• Develop and apply both first principles:based and data:driven techniques to solving complex engineering problems.
• Perform data analysis on large, sparse, and noisy data.
• Perform uncertainty quantification and uncertainty propagation analyses.
• Test, validate, monitor, and maintain deployed ML models on field to ensure operational success.
• 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
nuclear, electrical engineering, mechanical, computer engineering, engineering physics, computational science, or a related field completed within the last 5 years
Preferred Qualifications:
• Basic understanding of ML methodologies and their applications to complex engineering systems.
• Experience with open:source machine:learning tools, such as TensorFlow, Keras, PyTorch, and MLflow.
• Experience with applying and deploying state:of:the:art machine:learning methods for solving complex engineering problems, including diagnostics and prognostics of complex engineered systems.
• Experience with sustainable machine:learning ecosystems, maintaining deployed machine:learning models on field, and adapting to evolving system conditions via continual learning app
Don’t miss out on new job openings!
Create a job alert for: Biology, Oak Ridge (TN)
It's free, and you can cancel email updates at any time