Postdoc: Multimodal Federated AI for Biomedical Discovery

Argonne National Laboratory; Illinois; On-site; USD 65,000 - 85,000; Full time

Job summary

Argonne National Laboratory seeks two postdoctoral researchers to help shape secure, scalable, and continuously learning AI systems for biomedical discovery. You will contribute to the Forge project, developing multimodal AI capable of learning across distributed data environments without centralizing sensitive data.

You'll work at the intersection of federated learning, foundation models, privacy-preserving ML, and continual learning, collaborating with scientists, software engineers, and HPC

Qualifications

• PhD completed within the last 0-5 years in a relevant field as listed.
• Strong Python programming and software development experience.
• Experience with ML/DL frameworks and federated learning concepts.

Responsibilities

• Conduct research in federated learning and multimodal AI for biomedical data.
• Develop methods for continual learning and adaptive federated training.
• Collaborate with computer scientists, domain scientists, and HPC experts; publish results.

Skills

Python programming

Experiment design

Communication of results

Interdisciplinary collaboration

Education

PhD in Computer Science / Data Science / Biomedical Informatics / Computational Biology / related field

Tools

PyTorch

TensorFlow

JAX

Job description

Argonne National Laboratory seeks two postdoctoral researchers to help shape secure, scalable, and continuously learning AI systems for biomedical discovery. You will contribute to the Forge project, developing multimodal AI capable of learning across distributed data environments without centralizing sensitive data.

You'll work at the intersection of federated learning, foundation models, privacy-preserving ML, and continual learning, collaborating with scientists, software engineers, and HPC