Machine Learning - Academic Graduate Appointee

We have an opening for a Machine Learning Academic Graduate Appointee. You will develop machine learning models under the guidance of staff members for the Advanced Sources and Detectors’ Scorpius linear accelerator project. These models will be used to help experimenters understand the behavior between the accelerator cells and the solid-state pulsed power system. The information obtained from these models will be used to devise algorithms that allow the control system to achieve optimal results at the accelerator cell that satisfy project requirements. This position is in the National Security Engineering Division (NSED), within Strategic Deterrence.

You will 

• Work under general guidance of physicists to understand the accelerator physics governing the fundamental operation of the linear accelerator.
• Conduct and organize large amounts of experimental data.
• Develop machine learning models to improve the understanding of the behavior of the accelerator cells with the solid-state pulsed power system.
• Characterize the performance and accuracy of the models  through statistical analysis, simulations, real-time experiments, etc.
• Collaborate with scientists, engineers, and technicians to accomplish research goals.
• Perform other duties as assigned.

• Ability to obtain and maintain a U.S. DOE Q-level security clearance which requires U.S. Citizenship.
• Bachelor’s degree in Computer Science, Mathematics, Physics or related field.
• Experience in scientific computing, algorithms, machine learning theory and application demonstrated by coursework, training, and/or work experience.
• Experience conducting and/or engaging in experiments for gathering sufficient data for machine learning.
• Sufficient verbal and written communication skills necessary to effectively collaborate in a team environment, document analyses and prepare, present and explain technical information and publications.
• Strong initiative, interpersonal skills, creativity, and ability to work in a collaborative, multidisciplinary team environment.           

Desired Qualification

• Master’s degree in Computer Science, Mathematics, Physics or related field.
• Previous LLNL internship experience relating to scientific computing, algorithms, and machine learning theory.
• Experience with C, C++ and/or Python.
• Experience with H5 and JSON file formats.
• Familiarity with popular machine learning libraries such as Keras, Tensorflow, PyTorch or related.
• Familiarity with a UNIX environment.
• Involement in software projects that follow the principles of Agile development.

#LI-Onsite

Position Information

This is a one-year Academic Graduate Appointee, open to those who have been awarded a degree at the time of the employment offer.

Why Lawrence Livermore National Laboratory?

• Included in 2024 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversity
• Our core beliefs - visit https://www.llnl.gov/diversity/our-values 
• Employee engagement - visit https://www.llnl.gov/diversity/employee-engagement

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.

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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.

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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. 

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