Machine Learning Algorithms - Postdoctoral Researcher

at  Lawrence Livermore National Laboratory

Company Description
Join us and make YOUR mark on the World!
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 important for continued success of the Laboratory’s mission.
Pay Range
$108,600 – $126,720 Annually
Please note that the pay range information is a general guideline only. Many factors are taken into consideration when setting starting pay including education, experience, the external labor market, and internal equity.
Job Description
We have an opening for a Postdoctoral Researcher to join our interdisciplinary team of Applied Machine Learning Researchers supporting a variety of application areas including Cyber Security, Climate Modelling, Energy Systems, Bioscience and Advanced Manufacturing. Qualified candidates should have a background in a scientific discipline providing underlying skills in data analytic techniques and a working knowledge of standard machine learning toolkits. While supporting applied research projects, selected candidates will be provided mentorship, practical training and skill development to develop depth and breadth in machine learning techniques as well as gain exposure to a variety of application areas. This position is in the Computational Engineering Division (CED) within the Engineering Directorate.
In this role you will
Conduct research into state-of-the-art Machine Learning algorithms relevant to the problem being addressed.
Implement, train and validate proposed algorithms for specific problem domains.
Contribute to the integration of algorithms within larger programmatic systems that require these capabilities.
Collaborate with others in a multidisciplinary team environment to accomplish research goals.
Pursue independent, but complementary, research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings.
Travel as required to coordinate research with collaborators and visit field sites.
Perform other duties as assigned.
Qualifications
PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics or another technical discipline providing and underlying skillset in data analytic and machine learning techniques.
Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: robust deep learning, efficient machine learning, active learning, multimodal learning, and large language models.
Experience in the broad application of one or more higher-level programming languages such as Python, Java/Scala, Matlab, R or C/C++.
Experience with one or more deep learning libraries such as TensorFlow, PyTorch, Keras, Caffe or Theano.
Ability to undertake original research and first-authored publications at peer-reviewed conferences, such as NeurIPS, ICLR, and similar venues.
Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.
Additional Information
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)
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Employee engagement - visit https://www.llnl.gov/diversity/employee-engagement
Security Clearance
This position requires either no security clearance, or a Department of Energy (DOE) L-level or Q-level clearance depending on the particular assignment.
If you are selected and a security clearance is required, 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. L and Q-level clearances require U.S. citizenship.
If no security clearance is required, but 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.
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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
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Please refer the Job description for details