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source

Xiaojing Gao

Top university

1 month ago

Computational Postdoc in Foundation Models for Intrinsically Disordered Proteins Stanford University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

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Country

United States

University

Stanford University

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Keywords

Computer Science
Machine Learning
Chemistry
Biomedical Engineering
Biology
Artificial Intelligence
Computational Biology
Synthetic Biology
Biochemical Engineering

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About this position

Stanford University’s SynBioGaoLab is advertising a computational postdoc focused on foundation models and sequence-structure-function studies of intrinsically disordered proteins. The project is described as part of a consortium using unique large datasets and an interdisciplinary team that bridges several labs.

This opportunity is especially relevant for researchers with experience in machine learning, AI, protein design, and protein analysis. The post emphasizes computational work at the intersection of biology and computer science, with a strong biomolecular engineering/synthetic biology flavor.

The announcer is Xiaojing Gao, Assistant Professor at Stanford University. The post invites interested candidates to email the lab directly, but no formal application portal, deadline, or funding details are provided in the text.

If you are looking for a postdoctoral role in AI for biology, protein modeling, or data-driven biomolecular research, this appears to be a strong fit.

Funding details

Available

What's required

Ideal candidates have led ML/AI projects in protein design or protein analysis. The role is for a computational postdoc working on foundation models and sequence-structure-function studies of intrinsically disordered proteins, and the team is looking for someone comfortable working in an interdisciplinary consortium across several labs.

How to apply

Email the lab to express interest and apply. The post does not provide a formal portal or deadline.

More information can be found here

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