Immune repertoires represent a vast and diverse collection of T and B cell receptors which are able to interact with a seemingly infinite number of foreign pathogens. Recent advances in high-throughput sequencing enables us to quantify clonal selection and diversity of the adaptive immune response.
Keywords: bioinformatics, immune repertoires, b cell, evolution, t cell, immunology, systems immunology, adaptive immunity, computational immunology, phylogenetics, simulation
Immune repertoires represent a vast and diverse collection of T and B cell receptors which are able to interact with a seemingly infinite number of foreign pathogens. Recent advances in high-throughput sequencing enables us to quantify clonal selection and diversity of the adaptive immune response in the context of disease, infection, and healthy ageing. Furthermore, single-cell sequencing has provided an unprecedented resolution to which we can trace and quantify B and T cell repertoire evolution following cognate-antigen interactions. The increased usage of immune repertoire sequencing to study adaptive immunity has lead to numerous bioinformatics pipelines and tools. However, it remains largely uncharacterized whether biological conclusions (such as somatic hypermutation, clonal selection and clonal expansion) derived from single-cell sequencing data are robust to various computational inference pipelines.
We are seeking two master students for research projects (or theses) involving computationally modelling single-cell immune repertoires. While the majority of both projects would be computational, the opportunity to experimentally validate bioinformatic conclusions in the lab will be available towards the end of the project. All research infrastructure and future experiments will take 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. Given the current travel restrictions, it may be possible to work entirely remotely. Students should have experience with programming (preferably in R) and a basic understanding of immunology. The project/thesis should last at least 6 consecutive months of full-time work. To apply please send a CV, your earliest possible start date, and brief cover letter to Alex Yermanos (ayermano@ethz.ch).
Students can expect to obtain computational skills tailored to modelling single-cell immune repertoire sequencing data. This includes but is not limited to the following:
- Computationally analyzing single cell sequencing data
- Inferring B cell evolution using phylogenetic models
- Simulating immune repertoire dynamics and evolution
- Benchmarking various methods and tools commonly used to study immune repertoires
- Integrating experimental properties of immune repertoires (e.g. antibody affinity, antigen-specificity) with computational features.
For additional experimental projects profiling adaptive immunity please directly contact Alex Yermanos (ayermano@ethz.ch).
Immune repertoires represent a vast and diverse collection of T and B cell receptors which are able to interact with a seemingly infinite number of foreign pathogens. Recent advances in high-throughput sequencing enables us to quantify clonal selection and diversity of the adaptive immune response in the context of disease, infection, and healthy ageing. Furthermore, single-cell sequencing has provided an unprecedented resolution to which we can trace and quantify B and T cell repertoire evolution following cognate-antigen interactions. The increased usage of immune repertoire sequencing to study adaptive immunity has lead to numerous bioinformatics pipelines and tools. However, it remains largely uncharacterized whether biological conclusions (such as somatic hypermutation, clonal selection and clonal expansion) derived from single-cell sequencing data are robust to various computational inference pipelines.
We are seeking two master students for research projects (or theses) involving computationally modelling single-cell immune repertoires. While the majority of both projects would be computational, the opportunity to experimentally validate bioinformatic conclusions in the lab will be available towards the end of the project. All research infrastructure and future experiments will take 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. Given the current travel restrictions, it may be possible to work entirely remotely. Students should have experience with programming (preferably in R) and a basic understanding of immunology. The project/thesis should last at least 6 consecutive months of full-time work. To apply please send a CV, your earliest possible start date, and brief cover letter to Alex Yermanos (ayermano@ethz.ch).
Students can expect to obtain computational skills tailored to modelling single-cell immune repertoire sequencing data. This includes but is not limited to the following: - Computationally analyzing single cell sequencing data - Inferring B cell evolution using phylogenetic models - Simulating immune repertoire dynamics and evolution - Benchmarking various methods and tools commonly used to study immune repertoires - Integrating experimental properties of immune repertoires (e.g. antibody affinity, antigen-specificity) with computational features.
For additional experimental projects profiling adaptive immunity please directly contact Alex Yermanos (ayermano@ethz.ch).
Not specified
Applications and inquires can be sent directly to Alex Yermanos (ayermano@ethz.ch)
Applications and inquires can be sent directly to Alex Yermanos (ayermano@ethz.ch)