AI/ML Computational Biologist - Postdoctoral Researcher

About the role

The successful candidate will conduct research at the intersection of artificial intelligence (AI), machine learning (ML), and computational biology. Research will focus on understanding host-response dynamics in complex biological systems using large-scale multiomic datasets.

Responsibilities

• Develop and apply machine learning methods for prediction and representation learning from high-dimensional biological data.
• Contribute to the design and implementation of workflows for integrative analysis of multiomic datasets (bulk, single-cell, spatial, and multimodal).
• Investigate, develop, and apply approaches for 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.

Requirements

• PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, Data Science, or a related field.
• Strong background in machine learning, statistical modeling, computational biology, or a related quantitative discipline.
• Experience analyzing high-dimensional biological data such as genomics, transcriptomics, or related modalities.
• Proficiency in Python and R.
• Experience with ML frameworks such as PyTorch, TensorFlow, or similar.
• Familiarity with Linux/Unix and scientific computing workflows.
• Demonstrated ability to conduct high-quality research and publish results in peer-reviewed journals.
• Demonstrated ability to work effectively in a collaborative research environment.
• Strong written and verbal communication skills.

Qualifications

• PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, Data Science, or a related field.
• Strong background in machine learning, statistical modeling, computational biology, or a related quantitative discipline.
• Experience analyzing high-dimensional biological data such as genomics, transcriptomics, or related modalities.
• Proficiency in Python and R.
• Experience with ML frameworks such as PyTorch, TensorFlow, or similar.
• Familiarity with Linux/Unix and scientific computing workflows.
• Demonstrated ability to conduct high-quality research and publish results in peer-reviewed journals.
• Demonstrated ability to work effectively in a collaborative research environment.
• Strong written and verbal communication skills.

Skills

• Experience with deep learning or probabilistic modeling approaches, such as variational autoencoders, scVI, or related methods.
• Experience with single-cell, spatial, and/or multimodal omics data.
• Experience with multiomic data integration, including multimodal single-cell datasets.
• Experience with transfer learning, domain adaptation, cross-dataset integration, or batch correction.
• Experience with transformers, self-supervised learning, or pretrained models for biological data.
• Experience training and scaling machine learning models on large datasets.
• Interest in immunology, host-pathogen biology, or disease modeling.

Benefits

Lawrence Livermore National Laboratory offers a comprehensive benefits package including:

• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules

Pay

$123,048 Annually

Schedule

Full-time

Benefits

Lawrence Livermore National Laboratory offers a comprehensive benefits package including:

• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules

Additional Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.

Why Lawrence Livermore National Laboratory?

- Included in 2026 Best Places to Work by Glassdoor!

Equal Employment Opportunity

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