Machine Learning - Postdoctoral Researcher
Machine Learning - Postdoctoral Researcher
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Job Description
Were looking for a Machine Learning Postdoctoral Researcher to contribute to fundamental R&D in machine learning and statistical methods in support of different projects related to AI Safety & Security Foundation Models in areas such as material science or bio assurance and uncertainty quantification for deep learning models. These will be interdisciplinary projects that aim to combine state-of-the-art machine learning models with various science objectives. Examples are multi-modal sequence-to-sequence models for molecules and chemical reactions or combine large language models with other modalities. Furthermore you will develop methods to improve safety and trustworthiness of these models. This position will be in the Machine Intelligence Group in the Center for Applied Scientific Computing (CASC) Division within the LLNL Computing Directorate.
You will
- Research design implement and apply advanced machine learning methods for multiple applications in a collaborative scientific environment.
- Actively participate with project scientists and engineers in defining planning and formulating experimental modeling and simulation efforts for complex problems stemming from national security applications.
- Propose and implement advanced analysis methodologies collect and analyze data and document results in technical reports and peer-reviewed publications.
- Contribute to grant proposals and collaborate with others in a multidisciplinary team environment including academic and industrial partners to accomplish research goals.
- Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
- Perform other duties as assigned.
Qualifications :
- Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA). See Additional Information section below for details.
- Recent Ph.D. in Machine Learning Optimization Computer Science Mathematics or a related field.
- Demonstrated ability and desire to obtain substantial domain knowledge in fields of application to enable effective communication with subject matter experts and to identify novel impactful applications of machine learning.
- Experience developing implementing and applying advanced statistical or machine learning models and algorithms using modern software libraries such as PyTorch TensorFlow or similar as evidence through medium to large scale deep learning models and experiments.
- Demonstrated research productivity as documented by publications reports presentations and/or open-source software in relevant venues (NeurIPS ICML ICLR CVPR AAAI AISTATS UAI KDD JMLR Nature etc.)
- Experience with scientific programming in the Python ecosystem as evidence through software artifacts such as deep learning models workflows simulations or similar
- Experience with one or more of the following areas of deep learning: large language models graph neural networks multimodal models generative models robustness explainable AI
Qualifications We Desire
- Experience with high-performance computing GPU programming parallel programming cloud computing and/or related methods including running numerical simulations of complex workflows
- Demonstrated technical leadership in fields related to machine learning such as mentorship or managing teams.
- Experience or interest in scientific applications such as material science climate science etc.
Additional Information :
#LI-Hybrid
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 2025 Best Places to Work by Glassdoor!
- Flexible Benefits Package
- 401(k)
- Relocation Assistance
- Education Reimbursement Program
- Flexible schedules (*depending on project needs)
- Our values - visit 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.)
National Defense Authorization Act (NDAA)
The 2025 National Defense Authorization Act (NDAA) Section 3112 generally prohibits citizens of China Russia Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position Candidates must be eligible to access the Laboratory in compliance with Section 3112.
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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Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
