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Xiaojing Gao

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

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available
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Country

United States

University

Stanford University

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Keywords

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

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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

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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