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Predicting immune escape of SARS-COV-2 variants from human antibodies with deep learning models
We are seeking master students for research projects or theses involving antibody expression, screening of SARS-COV-2 receptor binding domain (RBD) yeast library with antibodies through SARS-COV-2 infection, and application of machine learning on the generated data.
The project will last preferably 6 months. All research takes place in the Lab for Systems and Synthetic Immunology at the ETH Zurich, Department of Biosystems Science and Engineering in Basel (https://bsse.ethz.ch/lsi) in the lab of Professor Sai Reddy. Students can expect to obtain experimental skills involving antibody expression, yeast display, high-throughput sequencing library preparation, computational skills in deep learning, and biological data analysis.
Related publication:
https://www.sciencedirect.com/science/article/pii/S0092867422011199
The project will last preferably 6 months. All research takes place in the Lab for Systems and Synthetic Immunology at the ETH Zurich, Department of Biosystems Science and Engineering in Basel (https://bsse.ethz.ch/lsi) in the lab of Professor Sai Reddy. Students can expect to obtain experimental skills involving antibody expression, yeast display, high-throughput sequencing library preparation, computational skills in deep learning, and biological data analysis. Related publication: https://www.sciencedirect.com/science/article/pii/S0092867422011199
Not specified
To apply, please send a CV, your earliest possible start date, and a brief cover letter regarding your interest and experience, to jiahan@ethz.ch).
To apply, please send a CV, your earliest possible start date, and a brief cover letter regarding your interest and experience, to jiahan@ethz.ch).
