1

Temporary Machine Learning Postdoc Jobs in California

Senior Machine Learning Engineer (LLM Evaluation & AI Agents) Location: Menlo Park, CA (Hybrid ... If eligible, the benefits available for this temporary role may include the following: • Medical ...

Postdoctoral Scholar

Bodega Bay, CA · On-site

$69K - $107K/yr

Deploy artificial Intelligence and machine learning to accelerate first-principles computation and ... Postdoctoral positions are paid on a step schedule per union contract and salaries will be ...

Showing results 21-40

Temporary Machine Learning Postdoc information

What is a temporary machine learning postdoc?

A Temporary Machine Learning Postdoc is a fixed-term research position, typically held at a university or research institution, focused on advancing knowledge and techniques in machine learning. Postdoctoral researchers in this role work on specific projects, often collaborating with faculty, graduate students, or industry partners. The position is designed to provide advanced training and research experience after earning a PhD, usually lasting from several months to a couple of years. Temporary postdocs may contribute to publishing academic papers, developing algorithms, and mentoring students, while preparing for longer-term academic or industry careers.

What skills and qualifications are needed to thrive as a temporary machine learning postdoc?

To thrive as a Temporary Machine Learning Postdoc, you need a PhD in a relevant field, a solid grasp of machine learning theory, and strong programming skills (often in Python or R). Experience with tools such as TensorFlow, PyTorch, and high-performance computing environments, as well as a record of peer-reviewed research, is typically required. Strong analytical thinking, collaboration, and effective communication help you stand out in this research-intensive role. These skills are essential for advancing cutting-edge research, publishing impactful findings, and contributing to interdisciplinary projects.

What types of projects and collaborations can a temporary machine learning postdoc expect to engage in?

A Temporary Machine Learning Postdoc typically works on cutting-edge research projects, often contributing to ongoing studies or initiating novel investigations within the field. Collaboration is common, both within their immediate research group and with interdisciplinary teams, such as data scientists, domain experts, or industry partners. Postdocs may also mentor graduate students, present findings at conferences, and publish papers, gaining valuable experience that can lead to academic or industry roles. The environment is fast-paced and research-driven, offering opportunities for professional growth and expanding one's research portfolio.

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

AspectTemporary Machine Learning PostdocData Scientist
CredentialsPhD in Computer Science, Data Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often requires experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageUniversities, research centersBusiness, technology, finance, healthcare
Search & Comparison IntentUnderstanding research-focused roles, academic opportunitiesIndustry roles, applied data analysis, business impact

The Temporary Machine Learning Postdoc is primarily research-oriented, often in academic or research settings, requiring a PhD. In contrast, a Data Scientist typically works in industry, applying data analysis and machine learning to solve business problems, often with a Bachelor's or Master's degree. Both roles involve machine learning skills but differ in environment, focus, and experience level.

What are the most commonly searched types of Machine Learning Postdoc jobs in California?

The most popular types of Machine Learning Postdoc jobs in California are:

What are popular job titles related to Temporary Machine Learning Postdoc jobs in California?

For Temporary Machine Learning Postdoc jobs in California, the most frequently searched job titles are:

What job categories do people searching Temporary Machine Learning Postdoc jobs in California look for?

The top searched job categories for Temporary Machine Learning Postdoc jobs in California are:

What cities in California are hiring for Temporary Machine Learning Postdoc jobs?

Cities in California with the most Temporary Machine Learning Postdoc job openings:

Full-time

Medical, Retirement, PTO

Re-posted 2 days ago


Job description

Berkeley Lab's Center for Advanced Mathematics for Energy Research Applications (CAMERA) has a new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities. 

This role involves research and development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction of 3D+ structure, heterogeneity, and/or dynamics from scattering and/or microscopy data; (2) autonomous analysis and decision making for self-driving and/or human-in-the-loop experiments; (3) computer vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial intelligence to analysis of experimental data. Of particular interest will be new approaches for tackling multimodal data, quantifying uncertainty, providing rigorous theoretical guarantees, and modelling complex physics, noise processes, and measurement error. You will work closely with mathematicians, software engineers, physicists, materials scientists, and beamline scientists to implement these new tools on HPC computer architectures and deliver them as user-friendly software to meet DOE experimental facility needs.

We're here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!

Why join Berkeley Lab?

We invest in our employees by offering a total rewards package you can count on:

  • Exceptional health and retirement benefits, including pension or 401K-style plans

  • A culture where you'll belong - we are invested in our teams! 

  • In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year.

  • Parental bonding leave (for both mothers and fathers)

You will:

  • Conduct independent and collaborative research to develop new mathematics and algorithms for analyzing complex data from DOE experimental facilities.

  • Develop new mathematical algorithms targeting one or more focus areas: (1) 3D+ reconstruction of structure/heterogeneity/dynamics from scattering and/or microscopy data; (2) autonomous analysis and decision-making for self-driving and/or human-in-the-loop experiments; (3) computer vision for extracting patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms that enable new reliable new applications of machine learning and artificial intelligence to experimental data analysis.

  • Make advances in one or more of: multimodal data fusion/joint inference; uncertainty quantification with realistic noise/measurement error; complex physics- and artifact-aware forward modeling; and theory-grounded guarantees for proposed algorithms.

  • Collaborate with scientific users and experimentalists at DOE experimental facilities to apply the developed software to real datasets and meet their scientific needs.

  • Publish results in peer-reviewed venues, present at conferences/workshops, and contribute to CAMERA's collaborative research activities.

 

We are looking for:

  • Ph.D. in Applied Mathematics, Computer Science, Physics, or related field.

  • Strong research track record developing advanced mathematical and computational methods for analyzing complex experimental or imaging data.

  • Demonstrated expertise in several of the following areas: inverse problems, statistics, optimization, uncertainty quantification, and/or computer vision/machine learning.

  • Strong foundation in at least one of: numerical linear algebra, Fourier/spectral methods, scientific computing, and/or high-performance computing.

  • Proven ability to publish in peer-reviewed venues and present research at seminars, workshops, and scientific conferences.

  • Excellent written and verbal communication skills, with the ability to contribute effectively to large, collaborative, multidisciplinary projects in a diverse environment.

 

Desired skills/knowledge:

  • Familiarity with modern machine learning methods and software, including experience applying them to scientific or experimental datasets.

  • Experience collaborating with domain scientists to analyze real experimental data and translate scientific questions into robust, actionable computational approaches.

Additional information:

  • Applications will be accepted until the job posting is removed.

  • Appointment type: This is a full-time, 2 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.

  • Salary range: The salary range for this position is $8,570 - $9,935 and is expected to start at $8,570 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries will be predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral experience.

  • Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

  • Work modality: Work may be performed on-site, hybrid. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.

  • Union Represented: This position is represented by a union for collective bargaining purposes.

Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov

Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.

Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.