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Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory’s mission.

Pay

$113,760 Annually

We are excited to offer an opportunity for a Postdoctoral Researcher to research and develop on machine learning algorithms for local seismic event discrimination and induced seismicity forecasting. This posting is within LLNL’s Seismology Group with close integration with LNNL’s Computational Geosciences Group. You will support the RECONNECT (Real-time inducEd seismiCity fOrecasts learNiNg sEismic CaTalogs) project in collaboration with industrial partners. You will be expected to apply your expertise to design machine learning models to detect and discriminate seismic events in near real-time and utilize catalogs for induced seismicity forecasting to facilitate decision-making in application areas such as geologic carbon storage and geothermal energy production. This position requires a background in seismology and machine learning and knowledge of computer programming and/or software development. The successful applicant will have access to LLNL's extensive computer facilities and field data. You will interact with professional colleagues, mid-level management and sponsors across and outside of the Laboratory. 

In this role you will  

• Conduct original and independent research, in collaboration with other LLNL researchers to improve our understanding of earthquakes and other natural or anthropogenic signals contained in continuous seismic waveforms and/or induced seismicity forecasting,  
• Design and implement real-time machine learning approaches to classify local seismic events and reduce false detections in machine learning-based seismic detection and location pipelines 
• Develop modern, flexible, and efficient visualization tools/packages for induced seismicity decision making.   
• Present research at meetings, as well as write, illustrate, and publish results in peer reviewed journals. 
• Work as part of a scientific team and interact with other researchers to design and implement research projects, while coordinating program requirements and deliverables for sponsors, including program reviews and technical reports. 
• Travel to assist with experiment execution, data collection, to interact with collaborators, sponsors and research customers and to present results at scientific meetings. 
• Perform other duties as assigned. 

•  Creativity, ability, and knowledge in quantitative seismology and signal processing. 
• Experience in machine learning applied to seismological applications. 
• Proficiency in organizing and analyzing databases of waveforms, events, amplitudes, and arrivals for performing quantitative analyses. 
• Experience with programming in Python and/or other programming languages (e.g. Java, C/C++, fortran) and experience with heterogeneous computing environments (Mac or PC, UNIX or LINUX platforms). 
• Ability to interact effectively with a team of interdisciplinary scientists having different backgrounds. 
• Proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present, explain and publish technical information. 
• Ability to travel internationally as needed. 

Qualifications We Desire 

• Strong background in machine learning applications related to seismology, specifically related to detection, phase picking, association, location (e.g. public algorithms including GAMMA, PhaseNet, EarthWorm, HypoInverse, HypoDD, GrowClust, etc.,) 
• Experience with principles of earthquake forecasting and seismic hazard analysis.
• Experience with object-oriented programming in Python, Java, and/or C++ . 

• Familiarity with modern software development process (e.g. git, continuous integration for automated testing, etc.),
• Experience collaborating with industrial operators, service companies, and/or international colleagues. 

All your information will be kept confidential according to EEO guidelines. 

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.

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

None required.  However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  (This process does not apply to foreign nationals.) 

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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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.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.

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. 

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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.