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Weekend Machine Learning Postdoc Jobs in Santa Clara, CA

... in machine learning and/or statistical methods with experience in developing new approaches • Training and research experience (preferably at postdoctoral level) in at least one of the following ...

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Weekend Machine Learning Postdoc information

What is a Weekend Machine Learning Postdoc?

A Weekend Machine Learning Postdoc is a postdoctoral researcher who focuses on machine learning projects and typically works on weekends or has a flexible schedule that includes weekend hours. This role often involves conducting advanced research in machine learning, developing algorithms, publishing papers, and collaborating with academic or industry teams. Weekend postdoc positions may be ideal for those balancing other commitments or seeking non-traditional work hours while continuing their research careers.

What are the typical projects and collaboration opportunities for a Weekend Machine Learning Postdoc?

As a Weekend Machine Learning Postdoc, you will often contribute to ongoing research projects, developing and refining machine learning models in collaboration with faculty, graduate students, and occasionally industry partners. While your hours are concentrated on weekends, you’ll typically participate in regular research meetings, code reviews, and may co-author papers or grant proposals. The role provides opportunities to mentor junior researchers and expand your expertise by working on interdisciplinary teams. This structure allows you to make significant research contributions while maintaining flexibility in your schedule.

What are the key skills and qualifications needed to thrive as a Weekend Machine Learning Postdoc, and why are they important?

To thrive as a Weekend Machine Learning Postdoc, you need a strong background in machine learning, statistics, and programming, typically supported by a PhD in a relevant field. Experience with tools such as Python, TensorFlow, PyTorch, and data analysis platforms, as well as familiarity with academic research methodologies, is essential. Exceptional problem-solving abilities, self-motivation, and effective communication are vital soft skills for success in research and collaboration. These skills enable you to drive innovative research, efficiently manage independent projects, and contribute meaningful insights to the field.

What is the difference between Weekend Machine Learning Postdoc vs Weekend Data Scientist?

AspectWeekend Machine Learning PostdocWeekend Data Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentAcademic research settings, universities, research labsIndustry companies, startups, consulting firms
Employer & Industry UsageResearch institutions, universities, academic grantsTech companies, finance, healthcare, retail
Common Search & ComparisonYesYes

The Weekend Machine Learning Postdoc typically involves academic research with a focus on advancing machine learning theories and models, often requiring a PhD. In contrast, a Weekend Data Scientist applies data analysis and machine learning techniques in industry settings, often with a bachelor's or master's degree. Both roles may work on similar projects but differ mainly in their environment, credentials, and end goals.

What are the most commonly searched types of Machine Learning Postdoc jobs in Santa Clara, CA?

The most popular types of Machine Learning Postdoc jobs in Santa Clara, CA are:

What are popular job titles related to Weekend Machine Learning Postdoc jobs in Santa Clara, CA?

For Weekend Machine Learning Postdoc jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Weekend Machine Learning Postdoc jobs in Santa Clara, CA look for?

The top searched job categories for Weekend Machine Learning Postdoc jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Weekend Machine Learning Postdoc jobs?

Cities near Santa Clara, CA with the most Weekend Machine Learning Postdoc job openings:

Infographic showing various Weekend Machine Learning Postdoc job openings in Santa Clara, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Atomistic and Data-Driven Modeling of Materials for Energy Applications - Postdoctoral Researcher

LLNL

Livermore, CA

$136K/yr

Full-time

Retirement

Posted 7 days ago


Job description

Company Description

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. 

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

Job Description

We have multiple openings for Postdoctoral Researcher Positions to conduct mentored research in atomistic and data-driven modeling of materials for energy applications. Key focus areas include investigating reactivity, transport, and phase evolution at heterogeneous interfaces; predicting materials degradation and coupled chemo-electro-mechanical response under operating conditions; understanding electronic properties of materials under non-equilibrium conditions; and developing data science approaches for predicting materials performance across scales. You will work closely with a multidisciplinary team in support of projects sponsored by the Basic Energy Sciences, Transportation Technologies Offices, and Office of Electricity within the Department of Energy, and internal LDRD programs. This position is within the Quantum Simulations Group within the Materials for Emerging Applications and Extreme Conditions section of the Materials Science Division in the Physical and Life Sciences Directorate.

This position requires full-time on-site presence due to the nature of the work.

Note:  This is a two-year Postdoctoral appointment with the possibility of extension to a maximum of three years. Eligible candidates are recent PhDs within five years of the month of the degree award at time of hire date.

You will 

  • Perform electronic structure theory-based simulations of complex materials, such as oxides and multi-element systems.
  • Perform thermodynamic and kinetic analyses of chemical reactions and phase transitions at surfaces and interfaces.  
  • Perform non-equilibrium molecular dynamics simulations & first-principles calculations to study materials response under externally applied stimuli.
  • Derive structure-composition-property relationships using statistical, analytical, and machine-learning based methodologies.
  • Develop machine-learning interatomic potentials and surrogate models based on physics-informed descriptors for property evaluation and prediction.
  • Contribute to the planning, design, and execution of assigned research activities under the guidance of senior scientists and project leadership. Collaborate with computational and experimental scientists in a multidisciplinary team environment to accomplish research goals.
  • Develop increasing technical independence while pursuing research activities aligned with project and program goals; interact with collaborators within and outside the Laboratory. Document research, contribute to peer-reviewed publications, and present results within the DOE community and at conferences/technical meetings.
  • 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.
  • Ph.D. degree completed, or anticipated to be completed by the hire date, in Materials Science, Chemistry, Physics, Mechanical Engineering or a related field.
  • Experience in the application of density functional theory and/or advanced electronic structure theory for simulating complex materials, including oxides and multi-element systems
  • Experience performing large-scale molecular dynamics simulations on high-performance computing environments.
  • Additional experience in at least one of the following methods: machine-learning based approaches, cluster expansion, advanced statistical analysis, kinetic Monte Carlo simulations, phase-field modeling, reduced order, descriptor or surrogate model development as relevant to energy related applications.
  • Ability to perform technical assignments with increasing independence, analyze results, and contribute to solutions for defined research problems. Ability to contribute to research directions under mentorship and communicate results effectively through peer-reviewed publications and technical presentations. Proficient verbal and written communication skills to collaborate effectively in a team environment, prepare written reports and present and explain technical information.
  • Interpersonal skills necessary to interact with scientists, engineers and other technical and administrative staff in a collaborative, multidisciplinary team environment.

Qualifications We Desire

  • Experience with computational workflow development and multiscale model integration
  • Experience in modeling highly disordered materials and/or heterogeneous interfaces
  • Experience with AI/ML-enabled materials discovery, surrogate modeling, and generative models.
  • Experience with Bayesian optimization, uncertainty quantification, sensitivity analysis, and Pareto front analysis.
  • Experience supporting DOE consortia or multi-laboratory data integration efforts.

Pay Range

$123,048 Annually

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting.  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

#LI-Onsite

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 2026 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 https://www.llnl.gov/inclusion/our-values

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.  

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.

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.