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 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:
Postdoctoral Fellow, Multimodal Modeling
Chicago, IL · On-site
$84K/yr
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:
Postdoctoral Fellow, Multimodal Modeling
Chicago, IL · On-site
$84K/yr
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:
Graph Neural Network information
See Norridge, IL salary details
$14.85 - $17.03
2% of jobs
$17.03 - $19.21
8% of jobs
$19.21 - $21.39
9% of jobs
$22.38 is the 25th percentile. Wages below this are outliers.
$21.39 - $23.57
11% of jobs
The median wage is $25.27 / hr.
$23.57 - $25.75
24% of jobs
$25.75 - $27.92
19% of jobs
$28.20 is the 75th percentile. Wages above this are outliers.
$27.92 - $30.10
8% of jobs
$30.10 - $32.28
6% of jobs
$32.28 - $34.46
4% of jobs
$34.46 - $36.64
4% of jobs
$36.64 - $38.81
3% of jobs
$14
$26
$38
How much do graph neural network jobs pay per hour?
What are the key skills and qualifications needed to thrive in the graph neural network position, and why are they important?
To excel as a Graph Neural Network Engineer, you need a strong background in machine learning, graph theory, neural networks, and proficiency in programming languages such as Python. Familiarity with deep learning frameworks like PyTorch or TensorFlow, and experience with specialized libraries such as DGL or PyTorch Geometric are highly valued. Excellent problem-solving skills, teamwork, and the ability to communicate complex concepts to both technical and non-technical stakeholders will help you stand out. These combined abilities enable professionals to design, implement, and deploy cutting-edge GNN models that address complex, real-world data-structure challenges across various industries.
What does a typical project workflow look like for a graph neural network engineer?
A typical project workflow for a Graph Neural Network Engineer involves collaborating with data scientists and domain experts to understand the problem, preprocessing and visualizing graph-structured data, and selecting appropriate model architectures. The role often includes building, training, and evaluating GNN models, iterating on hyperparameters, and deploying models to production environments. Throughout the process, you will engage in code reviews, document findings, and present results to stakeholders. Teamwork and effective communication are essential, as projects frequently require close collaboration with researchers, software engineers, and business units to ensure solutions meet practical needs and performance goals.
What is a graph neural network?
A Graph Neural Network (GNN) job typically involves designing, implementing, and optimizing neural network models that operate on graph-structured data. Professionals in this role apply GNNs to tasks like recommendation systems, fraud detection, social network analysis, and molecular property prediction. Responsibilities often include data preprocessing, model architecture selection, training, evaluation, and deployment. Strong knowledge of machine learning, deep learning frameworks (such as PyTorch or TensorFlow), and graph theory is essential.
$84K/yr
Full-time
Retirement, PTO
Posted 24 days ago
Job description
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 OpportunityThe 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
- 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
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 YouWe'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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