AI/ML Computational Biologist - Postdoc (Multi-Omics)

Lawrence Livermore National Laboratory; Livermore (CA); On-site; USD 105,000 - 142,000; Full time

Job summary

Lawrence Livermore National Laboratory (LLNL) invites applications for an AI/ML Computational Biologist - Postdoctoral Researcher in Livermore, CA. This two-year term appointment (potential extension to three) focuses on integrating AI/ML with multi-omics to study host-response dynamics and disease progression, with access to high-performance computing.

The role emphasizes collaboration, publication, and training in self-supervised and foundation models, with a stipend commensurate with

Qualifications

• PhD in Computational Biology or related field.
• Strong background in ML and statistical modeling.
• Experience with high-dimensional omics data.

Responsibilities

• Develop and apply machine learning methods for prediction and representation learning from high-dimensional biological data.
• Design workflows for integrative analysis of multiomic datasets.
• Investigate multimodal data fusion, cross-dataset integration, and transfer learning.
• Train, adapt and evaluate self-supervised and foundation models for omics data.
• Develop and apply interpretable models linking molecular states to disease trajectories and host-response phenotypes.
• Process and analyze large-scale sequencing and other omics datasets.
• Present research findings at seminars, conferences, and technical meetings.
• Contribute to research design and project execution.
• Collaborate in a multidisciplinary team environment.
• Publish results in peer-reviewed journals.
• Perform other duties as assigned.

Skills

Python

R

Machine learning

Statistics

Collaboration

Education

PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, Data Science, or related field

Tools

PyTorch

TensorFlow

Linux

Unix

Job description

Lawrence Livermore National Laboratory (LLNL) invites applications for an AI/ML Computational Biologist - Postdoctoral Researcher in Livermore, CA. This two-year term appointment (potential extension to three) focuses on integrating AI/ML with multi-omics to study host-response dynamics and disease progression, with access to high-performance computing.

The role emphasizes collaboration, publication, and training in self-supervised and foundation models, with a stipend commensurate with