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Postdoctoral Fellow Machine Learning Jobs in Chicago, IL

Late-stage PhD student or postdoc in a quantitative or computational field * Hands-on experience ... Familiarity with modern machine learning approaches (e.g., deep learning, generative models, or ...

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Postdoctoral Fellow Machine Learning information

See Chicago, IL salary details

$25.8K

$60.8K

$86K

How much do postdoctoral fellow machine learning jobs pay per year?

As of Aug 6, 2026, the average yearly pay for postdoctoral fellow machine learning in Chicago, IL is $60,801.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $68,500.00 per year, depending on experience, location, and employer.

What is a postdoctoral fellow in machine learning?

A Postdoctoral Fellow in Machine Learning is a researcher who has recently completed their PhD and is engaged in advanced research in the field of machine learning. This role typically involves conducting independent or collaborative research, publishing scientific papers, and sometimes mentoring students. Postdoctoral fellows often work at universities, research institutes, or industry labs, focusing on developing new algorithms, improving existing models, or applying machine learning techniques to specific problems. The position is usually temporary, lasting one to three years, and aims to prepare researchers for permanent academic or industry roles.

What is the difference between Postdoctoral Fellow Machine Learning vs Postdoctoral Research Scientist?

AspectPostdoctoral Fellow Machine LearningPostdoctoral Research Scientist
Required credentialsPhD in Computer Science, Data Science, or related fieldPhD in relevant field, often with specialized research experience
Work environmentAcademic labs, universities, research institutionsResearch labs, industry R&D departments, tech companies
Employer and industry usagePrimarily academia, government researchPrimarily industry, corporate research divisions
Common search and comparison intentUnderstanding academic research roles in machine learningExploring industry-focused research career paths

Postdoctoral Fellow Machine Learning roles typically focus on academic research, requiring a PhD and working in universities or research institutions. In contrast, Postdoctoral Research Scientist positions are often industry-based, emphasizing applied research within corporate R&D departments. Both roles involve advanced machine learning expertise but differ mainly in work environment and career trajectory.

What are the key skills and qualifications needed to thrive as a postdoctoral fellow in machine learning?

To thrive as a Postdoctoral Fellow in Machine Learning, you need a strong background in computer science, mathematics, and statistics, typically supported by a PhD and relevant research experience. Familiarity with programming languages such as Python, machine learning frameworks like TensorFlow or PyTorch, and experience in high-performance computing environments are commonly required. Strong analytical thinking, effective scientific communication, and collaboration skills help you contribute to research teams and disseminate findings. These skills and qualities are crucial for advancing research, developing innovative solutions, and building a successful academic or industry career in machine learning.

What are some common challenges faced by postdoctoral fellows in machine learning, and how can they be addressed?

Postdoctoral Fellows in Machine Learning often encounter challenges such as balancing independent research with collaborative projects, staying current with rapidly evolving technologies, and securing funding or publishing in top-tier journals. To address these, it's helpful to establish clear communication with mentors and collaborators, set aside dedicated time for reading recent literature, and actively seek feedback on research drafts. Building a professional network through conferences and seminars can also open opportunities for collaboration and career advancement.
What are popular job titles related to Postdoctoral Fellow Machine Learning jobs in Chicago, IL? For Postdoctoral Fellow Machine Learning jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Postdoctoral Fellow Machine Learning jobs in Chicago, IL look for? The top searched job categories for Postdoctoral Fellow Machine Learning jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Postdoctoral Fellow Machine Learning jobs? Cities near Chicago, IL with the most Postdoctoral Fellow Machine Learning job openings:
Infographic showing various Postdoctoral Fellow Machine Learning job openings in Chicago, IL as of June 2026, with employment types broken down into 38% Full Time, and 62% Part Time. Highlights an 91% Physical, and 9% Remote job distribution, with an average salary of $60,801 per year, or $29.2 per hour.

Postdoctoral Fellow, Multimodal Modeling

Biohub

Chicago, IL

$84K/yr

Other

Retirement, PTO

Posted 20 days ago


Job description

The Team

Our decoding inflammation team builds tools to enable precise molecular-level measurements of inflammation within human tissues in real time, and develop proactive, early interventions that can be deployed when inflammation - which underlies the most significant causes of death worldwide - first flares in the body. You can learn more about our work here. 

Our team collaborates with three powerhouse universities - Northwestern University, the University of Chicago, and the University of Illinois Urbana-Champaign - to develop first-in-class technologies and make breakthroughs.

Our Vision

  • Pursue large scientific challenges that cannot be pursued in conventional environments
  • Enable individual investigators to pursue their riskiest and most innovative ideas
  • Facilitate research by scientists and clinicians at our home institutions and beyond

We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease. 

The Opportunity

The Chan Zuckerberg Biohub Chicago is seeking outstanding early-career scientists to join and participate in the launch of the Proteoform Spatial Biology Group by continuing their training as a Postdoctoral Fellow in Multimodal Modeling. The Proteoform Spatial Biology Group aims to uncover the spatiotemporal regulation of proteins and their unique molecular forms, proteoforms, in inflammation and autoimmunity. For this position, the ideal candidate is expected to have experience in working with multimodal and multiscale modeling of diverse datatypes across confocal microscopy images, mass spectrometry-based proteomics, phosphoproteomics, and/or interactomics.

What You'll Do
  • Design and train self-supervised multimodal models that fuse confocal protein imaging, single-cell protein proximity networks, and mass spectrometry-based phosphoproteomics into shared representations, using objectives such as reconstruction and contrastive alignment (e.g., CLIP)
  • Work with graph-structured proximity-network data, collaborating on graph- and topology-aware modeling approaches, and 
  • Leverage existing high-performing imaging models for feature extraction and inference, adapting them for co-embedding and building new image models where needed
  • Develop cross-modal alignment strategies relating surface organization to signaling and localization, and use the learned representations to model continuous cell-state structure and the features driving state transitions
  • Present findings internally and externally, and co-author publications
What You'll Bring
  • Essential:
    • PhD in machine learning, computational biology, bioengineering, biophysics, or a related field
    • Experience applying deep learning to images, including use of pretrained vision models
    • Demonstrated experience building both supervised and unsupervised models
    • Experience with multimodal modeling or data fusion across heterogeneous data types
    • Experience with graph neural networks or other graph/network representation learning
    • Proficiency in Python and modern deep learning frameworks (e.g., PyTorch, JAX, or TensorFlow)
  •  Nice to Have: 
    • Experience with contrastive or self-supervised learning (e.g., CLIP) for multimodal data
    • Familiarity with topology-aware or higher-order modeling (e.g., simplicial or motif-based methods)
    • Background in proteomics or mass spectrometry data analysis
    • Experience with sequencing-based or single-cell omics data analysis
    • Experience with microscopy or spatial imaging analysis in a biological setting
    • Fluency with immunology or single-cell state modeling
    • Experience building reproducible analysis pipelines and contributing to shared or open-source codebases
Compensation

The Chicago, IL base pay for a new hire in this role is $84,150. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

This position may be eligible to participate in our discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with our total rewards philosophy and may vary by role.

Benefits for the Whole You 

We're thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

  • Provides a generous employer match on employee 401(k) contributions to support planning for the future.
  • Paid time off to volunteer at an organization of your choice. 
  • Funding for select family-forming benefits. 
  • Relocation support for employees who need assistance moving

If you're interested in a role but your previous experience doesn't perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.

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