Job Summary General Atomics (GA), and its affiliated companies, is one of the world’s leading resources for high-technology systems development ranging from the nuclear fuel cycle to remotely piloted aircraft, airborne sensors, and advanced electric, electronic, wireless and laser technologies.
We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.
We currently have an exciting opportunity for a Scientist to join the Plasma Control Group in the Experimental Sciences Division of the DIII-D National Fusion Facility. The group conducts leading edge research for a range of facilities around the world, including the DIII-D facility in San Diego, and the ITER device in France.
The DIII-D National Fusion Facility is the U.S.’s principal magnetically confined fusion research facility, focusing on the exciting science of the burning plasma state and its control in preparation for fusion energy, developing the path to operation of future reactors. It has a strong focus on underlying science, and the application of this to improve fusion performance.
DUTIES & RESPONSIBILITIES:
- Design and develop machine learning and statistical inference models for control and operations optimization;
- Create sophisticated visualization, training, optimization, evaluation, and deployment pipelines using complex scientific data;
- Model physical and electronic systems for system optimization, control design, analysis, and simulation, including system identification through classical and machine learning methods;
- Design and deploy operational solutions applying machine learning models and control algorithms, for fusion and beyond;
- Disseminate work in recognized scientific journal publications, presentation at national and international level, pursuit of research projects, and collaborative work with and support of the wider DIII-D team in the above topic areas.
- Perform other duties as assigned or required.
Job Qualifications:
- Ph.D, Masters + 3 years, or Bachelor's + 5 years experience in one or more of: machine learning, signal analysis and information theory, plasma physics, tokamak operations and experiments, control theory, electromagnetics modeling and simulation, or similar related research.
- Extensive knowledge of machine learning techniques/algorithms (e.g. neural networks, random forests) and their statistical underpinnings.
- Extensive knowledge of machine learning techniques/algorithms (e.g. neural networks, random forests) and their statistical underpinnings.
- Proficient in Python, C/C++ and working knowledge of Matlab/Simulink.
- Experience using machine learning packages such as Tensorflow/Keras, PyTorch, Scikit-Learn.
- Experience working in a Linux-based environment.
- Source control proficiency using Git.
- Must have; (1) a thorough understanding of relevant scientific concepts, principles, and theory, particularly with regard to general machine learning and algorithms and fundamental physics principles; (2) experience demonstrating broad application of those concepts in real-world settings;
- Must possess the ability to; (1) understand new concepts quickly; (2) apply them accurately throughout an evolving environment; (3) organize, schedule, and coordinate work phases; and, (4) determine the appropriate approach at the task level or, with assistance, at the project level to provide solutions to a range of complex problems.
- Must have strong communication, computer, documentation, presentation, and interpersonal skills, ability to work independently and as part of a team; able to perform complex tasks in one scientific area; and, lead a team of less experienced professional employees on semi-routine tasks.
- Must have facility in moving rapidly from one task area to another, and ability to work extended hours and travel as required.
- Ability to communicate effectively with the scientific and engineering communities of DIII-D and collaborators, including written and oral technical presentations.
- Experience with operations and execution of experiments on magnetic plasma confinement devices
- Experience working with tokamaks including control and operational approaches to achieve physics goals; understanding and demonstrated experience in tokamak MHD equilibrium and stability physics;
- Experience with Bayesian optimization and experimental design.
- Experience with existing plasma analysis, simulation, and modeling tools such as TSC, Corsica, TRANSP, EFIT.
- Experience with real-time control systems, data acquisition, digitizers, signal conditioning, and data interpretation
- History of publication of original work(s) in professional scientific journals or formal technical equivalents
Willingness to adjust working hours in accordance with the schedules and needs of the Fusion Division.
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