Physics-Informed Machine Learning SpecialistLawrence Livermore National Laboratory • Livermore, California, United States

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Physics-Informed Machine Learning Specialist

Lawrence Livermore National Laboratory

Livermore, California, United States

Livermore, California, United States

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Über

Overview We have multiple openings for a Physics-Informed Machine Learning Specialist with a strong technical background in integrating artificial intelligence (AI) and machine learning (ML) methodologies with physics-based applications in engineering. You will combine existing AI/ML methodologies with state-of-the-art computational modeling and simulation capabilities on high performance computing (HPC) architectures to develop novel application areas within Lawrence Livermore National Laboratory's (LLNL) national security mission space. You will contribute to research and development in advanced simulation capabilities related to optimizing algorithms and models, surrogate model development, model validation, reliability, uncertainty quantification, and data engineering. You will work closely with other groups to support the missions of the Laboratory and with multidisciplinary teams and programmatic customers to ensure application needs are met. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate. These positions will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level. Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week. Responsibilities Provide technical leadership and guidance to project teams developing state of the art methods and applying research results to meet programmatic goals, while balancing priorities of customers and partners to ensure deadlines are met. Solve abstract and complex problems as required, using in-depth analysis, and drawing from advanced level technical knowledge, best practices, and both routine and innovative techniques and approaches. Serve as the primary technical point of contact for program managers internally and at sponsor and partner organizations by sharing relevant advanced level knowledge and providing opinions and recommendations on methodologies, as needed to fulfill deliverables and best meet sponsor needs. Utilize advanced level knowledge and skills and apply significant experience in one or more areas of computational science and engineering to new areas at the intersection of artificial intelligence and national security: computational mechanics, chemistry, physics, or materials, nuclear engineering, electrical engineering, non-destructive evaluation, robotics and control, optical systems, high performance computing, or other relevant area of computational science and engineering. Develop and apply complex algorithms in one or more machine learning areas/tasks to areas of national security: deep learning, unsupervised/self-supervised learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference, performance optimization, physics informed machine learning, agentic AI workflows. Perform other duties as assigned. Additional job responsibilities at the SES.4 level Establish and implement broad project vision and strategy and influence technical direction and decisions for self and others to drive successful project outcomes. Develop novel and innovative Engineering research, technologies, capabilities, and methodologies enabled by the use or integration of applied statistics, machine learning and artificial intelligence, and/or uncertainty quantification. Provide subject matter expertise and conduct highly complex and in-depth analysis within one or more areas of machine learning and artificial intelligence, applied statistics, and/or uncertainty quantification. Qualifications Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship. Master's degree in Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science or related technical field or the equivalent combination of education and related experience. Advanced level knowledge and significant experience in artificial intelligence, machine learning or data science, and developing applications in one or more of the following areas: mechanical engineering, aerospace engineering, computational mechanics, electrical engineering, applied statistics, uncertainty quantification, or a related technical area. Significant experience directing, leading, developing, and executing independent research projects. Advanced organizational, verbal and written communication, and interpersonal skills to collaborate effectively in a multidisciplinary team environment, and with subject matter experts, including authoring reports, presenting, and explaining complex technical information. Significant experience working effectively in a team environment with multi-disciplinary personnel while managing multiple concurrent tasks and deliverables. Additional qualifications at the SES.4 level Subject matter expertise of highly advanced concepts in machine learning or data science and significant experience developing applications in one or more of the following areas: physics, mechanical engineering, aerospace engineering, computational mechanics, electrical engineering, applied statistics, uncertainty quantification, or a related technical area. Significant experience and demonstrated ability to successfully lead technical personnel and projects and perform project planning and execution, including applying and developing creative and innovative solutions to highly complex problems. Expert communication, facilitation, interpersonal, and collaboration skills necessary to effectively lead a team, present and explain information, and influence and advise senior management and stakeholders, while positively representing the Program and the Laboratory. Qualifications We Desire Ability to obtain and maintain Sensitive Compartmented Information (SCI) access which requires U.S. citizenship. PhD in Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or a related technical field, or the equivalent combination of education and related experience. Significant experience developing, deploying, and/or utilizing multi-physics simulation codes for massively parallel, high-performance computing architectures utilized by DOE and DoD stakeholders. Pay Range $175,530 - $267,060 Annually $175,530 - $222,564 Annually for the SES.3 level $210,630 - $267,060 Annually for the SES.4 level This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee\'s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs. Additional Information Position Information This is a Career Indefinite position, open to Lab employees and external candidates. Security Clearance This position requires a Department of Energy (DOE) Q-level clearance. If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship. Pre-Employment Drug Test External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor. Wireless and Medical Devices Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices. If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings. How to identify fake job advertisements Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under "Find Your Job" of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond. To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf Equal Employment Opportunity We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws. Reasonable Accommodation Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. California Privacy Notice The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.
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Livermore, California, United States

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