Postdoc – ML for Protein Interaction Prediction

LLNL; Livermore (CA); Hybrid; USD 122,000 - 143,000; Full time

Job summary

Lawrence Livermore National Laboratory (LLNL) is seeking a Postdoctoral Researcher to advance computational structural biology, focusing on predicting protein-protein interactions in host-pathogen systems using deep learning.

You will work with DL-based methods, protein sequences, and structures, collaborating with computational and experimental biologists to push next-generation protein design tools and models forward.

Qualifications

• Experience developing and implementing deep learning models and algorithms.
• Experience with protein sequence and structure, bioinformatics, and structure modeling.
• Ability to work independently and in cross-disciplinary teams.
• Proven publication record or software releases demonstrating DL expertise.

Responsibilities

• Conduct research to design, analyze, and extend DL-based tools for protein interaction prediction.
• Develop sequence- and structure-computational frameworks and analysis tools.
• Collaborate with universities, industry, and national labs to advance simulation efforts.

Skills

Deep learning

Python

UNIX

HPC

Bioinformatics

Education

PhD in Life Sciences / Computational Biology

Tools

PyTorch

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Job description

Lawrence Livermore National Laboratory (LLNL) is seeking a Postdoctoral Researcher to advance computational structural biology, focusing on predicting protein-protein interactions in host-pathogen systems using deep learning.

You will work with DL-based methods, protein sequences, and structures, collaborating with computational and experimental biologists to push next-generation protein design tools and models forward.