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Multimodal Learning Jobs in Deerfield, IL (NOW HIRING)

Accenture

Senior Data Scientist

Chicago, IL · On-site

Design and implement deep-learning solutions using neural networks, transformers, convolutional architectures, sequence models, representation-learning techniques, and multimodal approaches. * Build ...

Tempus

Bioinformatics Scientist

Chicago, IL · On-site +1

Develop, tune, and optimize novel assays, algorithms, machine learning and statistical models to analyze next-generation sequencing (NGS) and multimodal data to detect oncology related biomarkers ...

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All JobsMultimodal Learning JobsMultimodal Learning Jobs in Deerfield, IL

Multimodal Learning information

See Deerfield, IL salary details

$21.4K

$62.7K

$116.4K

How much do multimodal learning jobs pay per year?

As of Sep 14, 2026, the average yearly pay for multimodal learning in Deerfield, IL is $62,737.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,700.00 and $73,200.00 per year, depending on experience, location, and employer.

What is multimodal learning?

Multimodal learning is an area of machine learning that involves integrating and processing information from multiple types of data, such as text, images, audio, and video. The goal is to create models that can understand and make predictions based on more than one data modality, similar to how humans use various senses. This approach is used in applications like speech recognition with visual cues, image captioning, and video analysis. By combining different data types, multimodal learning systems can achieve better accuracy and more robust understanding.

What are the key skills and qualifications needed to thrive in multimodal learning, and why are they important?

To excel as a Multimodal Learning Specialist, you need a solid background in machine learning, data science, and computer vision, often supported by an advanced degree in a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience integrating data from diverse sources (e.g., text, audio, images), and knowledge of relevant algorithms are crucial. Strong problem-solving abilities, creativity, and effective collaboration are standout soft skills for this role. These competencies are vital for developing innovative models that can process and interpret complex, multi-source data to drive impactful AI solutions.

What are some common challenges faced by professionals working in multimodal learning roles, and how can they be addressed?

Professionals in multimodal learning frequently encounter challenges related to integrating and aligning data from multiple sources, such as text, images, audio, or video. Ensuring data quality and consistency across modalities can be complex, and developing models that effectively combine heterogeneous information often requires advanced technical skills and innovative thinking. Collaboration with domain experts and other data scientists is key to overcoming these obstacles, as is staying up to date with the latest research and tools in machine learning. Regular team meetings and cross-disciplinary workshops can help foster a collaborative environment and promote knowledge sharing.

What is the difference between Multimodal Learning vs Data Scientist?

AspectMultimodal LearningData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or Computer ScienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness, tech companies, analytics teams
Industry UsageAI research, multimedia applications, roboticsData analysis, predictive modeling, business insights

Multimodal Learning focuses on developing AI models that process and integrate multiple data types like images, text, and audio. Data Scientists analyze data to extract insights, build models, and support decision-making. While both roles involve data and algorithms, Multimodal Learning is specialized in AI model development for complex data integration, whereas Data Scientists work broadly across data analysis and interpretation.

What are popular job titles related to Multimodal Learning jobs in Deerfield, IL?

For Multimodal Learning jobs in Deerfield, IL, the most frequently searched job titles are:

What cities near Deerfield, IL are hiring for Multimodal Learning jobs?

Cities near Deerfield, IL with the most Multimodal Learning job openings:

Multimodal Learning jobs near you
Infographic showing various Multimodal Learning job openings in Deerfield, IL as of September 2026, with employment types broken down into 56% Full Time, and 44% Contract. Highlights an 100% In-person job distribution, with an average salary of $62,737 per year, or $30.2 per hour.

Postdoctoral Fellow, Multimodal Modeling

Chicago, IL • On-site

Biohub
See more jobs at Biohubexternal

$84K/yr

Full-time

Retirement, PTO

Re-posted 29 days ago

Job description

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.
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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