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Tauhid Islam

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Postdoctoral Researcher in Genomics, Computational Biology, and Foundation Models at Stanford University Stanford University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Postdoctoral research position; funding details are not specified in the post.

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Country

United States

University

Stanford University

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Keywords

Computer Science
Biomedical Engineering
Biology
Computational Biology
Genomic
Statistics
Bioinformatic
Large Language Models
ML

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About this position

The Islam Lab at Stanford University is hiring a Postdoctoral Researcher to work at the intersection of genomics, computational biology, large language models (LLMs), foundation models, and multimodal AI.

The successful candidate will develop and apply foundation models to large-scale genomic and biomedical data. Research directions mentioned include biological sequence modeling, representation learning, multimodal data integration, generative AI for biology, and data-driven biological discovery.

Ideal applicants should hold a PhD in computational biology, bioinformatics, genomics, computer science, machine learning, or a related field. The post also asks for strong experience with deep learning, LLMs, foundation models, or biological sequence modeling, plus proficiency in Python and modern machine-learning frameworks. Experience analyzing large-scale genomic or biomedical datasets and a strong publication record are also expected.

The position is on-site at Stanford University in Stanford, California, United States. Start date is flexible. Funding details are not specified in the post.

To apply, send a CV, a brief research statement, and contact information for references to [email protected]. Informal inquiries are welcome.

Funding details

Postdoctoral research position; funding details are not specified in the post.

What's required

A PhD in computational biology, bioinformatics, genomics, computer science, machine learning, or a related field is required. Candidates should have strong experience with deep learning, LLMs, foundation models, or biological sequence modeling, proficiency in Python and modern machine-learning frameworks, experience analyzing large-scale genomic or biomedical datasets, and a strong publication record. Interdisciplinary research enthusiasm is preferred.

How to apply

Send a CV, a brief research statement, and contact information for references to [email protected]. Informal inquiries are welcome.

More information can be found here

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