Biohub

Postdoctoral Fellow, Multimodal Modeling

Chicago, IL (Onsite)

Sponsorship not specifiedDetected 6 days ago

PythonMachine LearningDeep LearningTensorFlowPyTorchData AnalysisCompensationBioinformaticsMicroscopyResearchMass SpectrometryCollaboration

About the role

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.

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)
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
Demonstrated experience building both supervised and unsupervised models
Experience building reproducible analysis pipelines and contributing to shared or open-source codebases
Provides a generous employer match on employee 401(k) contributions to support planning for the future.
Relocation support for employees who need assistance moving

Experience with multimodal modeling or data fusion across heterogeneous data types

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
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.
We're thankful to have an incredible team behind our work.

The Chicago, IL base pay for a new hire in this role is $84,150.
This position may be eligible to participate in our discretionary annual performance bonus program.

Paid time off to volunteer at an organization of your choice.
Funding for select family-forming benefits.
PhD in machine learning, computational biology, bioengineering, biophysics, or a related field
Experience applying deep learning to images, including use of pretrained vision models
Experience with graph neural networks or other graph/network representation learning

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.
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.

This listing is sourced directly from Biohub's careers page and normalized into a canonical job model.