Postdoctoral Fellow, Multimodal Modeling

The Proteoform Spatial Biology Group

The Proteoform Spatial Biology Group aims to uncover the spatiotemporal regulation of proteins and their unique molecular forms, proteoforms, in inflammation and autoimmunity.

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
• 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

• 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
• 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.

Benefits

We offer a wide range of benefits to support the people who make all we do possible, including a generous employer match on employee 401(k) contributions, paid time off to volunteer at an organization of your choice, funding for select family-forming benefits, and relocation support for employees who need assistance moving.