1

Temporary Machine Learning Postdoc Jobs in California

Postdoctoral Scholar

Bodega Bay, CA · On-site

$8.57K - $9.94K/mo

Perform research in machine learning methods based on control theory applied to problems in ... Postdoctoral positions are paid on a step schedule per union contract and salaries will be ...

next page

Showing results 1-20

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 cities in California are hiring for Temporary Machine Learning Postdoc jobs? Cities in California with the most Temporary Machine Learning Postdoc job openings:

Postdoctoral Fellow, Kelley Lab - Gene Regulation Machine Learning

Calico

South San Francisco, CA

$95K/yr

Other

Posted 10 days ago


Job description

Who We Are

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico's highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

The Calico Postdoctoral Fellowship Program

We are seeking ambitious early career scientists to join us in our mission to increase our understanding of the biology that controls human aging. This is a unique opportunity for individuals to distinguish themselves in aging research, deepen scientific training, and develop research independence.

The Postdoctoral Fellowship is a fixed-term educational assignment (three years with a potential fourth year extension) with rolling start dates. Postdoctoral Fellows are fully integrated into Calico's labs and community.

The program is designed to train individuals to become independent investigators in an academic or industry setting upon successful completion of the assignment. Fellows will receive regular feedback and guidance from their mentor(s) and participate in a formal annual review process to review project progress and individual performance and provide career coaching. 

Responsibilities

  • Lead Independent Research: Focus on their own project(s), which should pursue new research directions with dedicated resources for innovative and potentially high-risk/high-reward research
  • Contribute to Calico's Core Mission: Contribute to furthering an understanding of aging and age-related diseases
  • Drive Scientific Progress: Execute experiments meticulously, analyze data (including computational analysis if applicable) and troubleshoot procedures as needed
  • Publish Work: Generate work that is expected to be submitted for publication in a timely fashion upon completion of the assignment
  • Collaborate and Communicate: Actively collaborate across Calico's diverse teams and scientific community, including presenting progress and results to diverse audiences of computational scientists, lab scientists, and engineers
  • Professional Development: Engage with a community of other Postdoctoral Fellows and senior leadership through professional and career development opportunities, such as the annual Postdoc Summit, research-in-progress presentations, senior leader lunch sessions, and skill-building workshops

Position Requirements

The successful candidate will demonstrate characteristics valued across Calico's programs, including being a self-motivated team player, detail-oriented, extremely organized, and comfortable working on complex problems.

  • Education: Must have recently completed a PhD degree in a relevant scientific or computational field
    • Current PhD student applicants should be within 12 months of completing their PhD
    • Applicants who have already graduated must have completed their PhD within the past 3 years and not have been employed as a postdoc at more than one other lab/company since graduation
  • Experience: Must have made important contributions to science in their area, ideally demonstrated by having had a meaningful first author paper accepted for publication
  • Technical Versatility (General): While specific technical skills are project-dependent, proficiency in core scientific methodologies, analytical skills, and quantitative problem-solving is essential
  • Communication: Strong teamwork and communication skills are required
  • Adaptability: Must be flexible and able to respond quickly to shifting priorities, demonstrating a "can-do" attitude
  • Onsite Availability: Must be willing to work onsite five days per week

Application Requirements

The Postdoctoral Fellowship has four application components:

  • Research proposal (a 1-2 page creative and original research proposal on what you'd like to investigate in the Kelley Lab during your fellowship - note that project goals may evolve during the training period)
  • Updated CV with a full list of publications
  • Cover letter
  • List of 2-3 references that we may contact, including your PhD thesis advisor and any postdoctoral advisors (if applicable)

The estimated base salary for this role is $95,000. More information on our postdoctoral fellowship program can be found here.

About the Kelley Lab

Our group develops deep learning methods for regulatory genomics. The goal is a comprehensive model of the human cis-regulatory code that predicts how every nucleotide in the genome affects cell-type-specific gene regulation. We apply these models to predict genetic variant effects, amplifying insights from human genetics by boosting statistical power across the allele frequency spectrum, pinpointing causal variants, and generating mechanistic hypotheses.

Calico's structure means close collaboration with experimental groups and access to rich longitudinal phenotyping across large human cohorts, which lets us connect sequence-level predictions to outcomes that matter for aging. To fully leverage this, we seek highly quantitative, deeply curious, and intellectually courageous collaborative team players who thrive in a multidisciplinary environment. We welcome proposals that address core questions in the application of machine learning to derive insights from genomics, connecting sequence-level predictions to outcomes that matter for aging.

Publications from the group include:

  • Ziga Avsec et al., Effective gene expression prediction from sequence by integrating long-range interactions (2021) Nature Methods
  • Han Yuan & David R. Kelley, scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks (2022) Nature Methods
  • Johannes Linder, Divyanshi Srivastava, Han Yuan, Vikram Agarwal & David R. Kelley, Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation (2025) Nature Genetics