ZipRecruiter

Log In

1

Temporary Machine Learning Postdoc Jobs in California

LLNL

AI/ML Postdoctoral Researcher

Livermore, CA · On-site

$123K/yr

We are seeking an AI/ML Postdoctoral Researcher within our Laser Science and Systems Engineering ... Conduct research and development of an inverse pulse solve machine learning system by training ...

LLNL

AI/ML Postdoctoral Researcher

Livermore, CA · On-site

$123K/yr

We are seeking an AI/ML Postdoctoral Researcher within our Laser Science and Systems Engineering ... Conduct research and development of an inverse pulse solve machine learning system by training ...

Meta

Fundamental AI Researcher - FAIR

Menlo Park, CA

$154K/yr

Experience holding an industry, postdoctoral, faculty, or government researcher position * Research background in machine learning, artificial intelligence, computational statistics, applied ...

next page

Showing results 1-20

All JobsTemporary Machine Learning Postdoc JobsTemporary Machine Learning Postdoc Jobs in California

Temporary Machine Learning Postdoc information

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

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 during their appointment?

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 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 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:
Temporary Machine Learning Postdoc jobs near you

Postdoctoral Researcher, Zhou Lab

Arc Institute

Palo Alto, CA • On-site

$80K/yr

Full-time

Posted 11 days ago

Job description

About Arc Institute
Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.
Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.
Our two Institute Initiatives reflect this model in action:
  • Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets, accelerating the path from biological insight to clinical trials.
  • Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.
About the position
The Zhou Lab is looking for motivated, hard-working and curious applicants. Our expertise is in single-cell epigenomic modeling. We use high-throughput single-cell multiomic technologies and build computational models to study spatiotemporal dynamics of gene regulation.
The successful candidate will play a crucial role in advancing the state-of-the-art in generative AI applied to biology, including DNA sequence, gene regulation, and perturbation modeling. You will focus on developing ML models for biological data, leveraging frontier approaches such as novel ML architectures, interpretability techniques, and more. You will also apply your models for important computational biology applications in genome mining, molecular technology development, and invention of new therapeutic approaches.
This role is a unique opportunity to advance state-of-the-art machine learning in genomics and cell biology, contribute to high-impact scientific discoveries, and help define how computational approaches shape our understanding and engineering of biology. You will work in a highly collaborative team with expert experimental biologists to realize the full impact of your work, and also have the opportunity to contribute to Institute-wide machine learning efforts such as Arc's Virtual Cell Initiative.
Post-docs will be encouraged to lead independent projects resulting in high impact publications, present at conferences and prepare for long-term careers in academia or industry.
About you
  • You are passionate about developing machine learning models with real-world applications and scientific impact.
  • You have a strong understanding of modern deep learning, computational biology, and genetics.
  • You are known for your ability to analyze/visualize complex datasets, build high-quality ML tools, draw meaningful conclusions, and work effectively in a multidisciplinary team.
  • You are eager to learn and adapt new techniques.
  • You are intellectually independent and are able to design new research directions and projects with input from your PI.
  • You are excited about collaborating with a multidisciplinary team of experimental biologists and machine learning researchers at Arc.
  • You are familiar with recently reported projects in the fields of AI for genomics and biological design, including DNA sequence to function models, genome language models, and single-cell foundation models.

In this position you will
  • Train and evaluate state-of-the-art machine learning models for genomics
  • Design, perform, and analyze experiments for model applications
  • Keep appropriate experimental records and documentation
  • Analyze results with the Principal Investigator
  • Collaborate with postdocs, students, and employees on model development and data analyses
  • May mentor/train research associates, technicians, and students.
  • Publish, present, and represent the Zhou lab in journals and conferences.
  • Present at lab meetings, and participate in Arc-wide activities (seminars, science socials, symposiums, etc).

Requirements
  • Doctorate (MD, PhD) in Computer Science, Machine Learning, Computational Biology, Bioinformatics, Genetics/Genomics.
  • Excellent written and verbal communication skills.
  • Demonstrated ability to work in a fast-paced environment and be both an independent thinker and a highly collaborative team player.

How to Apply
Please submit:
  1. CV
  2. Brief cover letter describing your research interests, what kinds of projects you're excited to lead, and why the Zhou Lab is a fit. Please be sure to include contact information for 3+ references.

The minimum base salary for this position is $80,000. Base salary for this role is determined by how many months of relevant postdoctoral experience a successful candidate has. Base salary for this role is not negotiable.

Apply