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Clara Pavillet

BSc (Hons), MSc


DPhil Student

I am an interdisciplinary DPhil student from the Medical Sciences Doctoral Training Centre (MSDTC) and the Department of Biochemistry specialising in Computational Biology and Bioinformatics with Prof. Francesca Buffa and Prof. Tudor Fulga (Vice President, Gene Editing at Vertex Pharmaceuticals). I am a member of Keble College, and I am fully-funded by the University of Oxford and the Wellcome Trust.

Originally from France and having lived in South America and North America, I am fluent in French, Spanish and English. I graduated from the University of Toronto in 2016 with a BSc (Hons) in Biochemistry (concentration in Structural Biochemistry) and Immunology (concentration in Virology) taking a broad range of courses in both the physical and medical sciences. In parallel to my studies, I conducted research at the Hospital for Sick Children’s Peter Gilgan Centre for Research and Learning from 2014 to 2016. My undergraduate thesis under the supervision of Prof. Jean-Philippe Julien was on the HIV-1 glycoprotein, and structure-based protein design strategies to elicit neutralising antibodies against the virus (see more). My fascination with RNA viruses then led me to the Instituto de Investigaciones Biomédicas en Retrovirus y SIDA (INBIRS) at the University of Buenos Aires with Prof. Jorge Geffner and Dr. Federico Remes Lenicov.

Thereafter, I pursued graduate studies at the University of Oxford where I further combined an interest in systems biology, mathematical modelling, computer science and physics in a master's thesis supervised by Prof. Francesca Buffa before starting my DPhil in 2017. In the first year of my DPhil, I undertook three rotation projects in different research groups at the Department of Biochemistry1, Sir William Dunn School of Pathology2 and MRC WIMM Centre for Computational Biology3:

  • Machine Learning Approach to Analyse Single-Molecule Fluorescence In Situ Hybridization Images1 (see more)
  • Predicting Oxford Nanopore Base-Calling Errors to Improve the Performance of a Hidden Markov Model2 (see more)
  • Deep Learning Model to Predict tRNA Promoter and Processing Activities for gRNA Expression3 (see more)

My main DPhil project lies at the intersection of computer code (01) and genetic code (ACTG), bringing mathematical and computational sciences together to model the immune response and tackle disease. Specifically, I am investigating T cell-mediated immune responses using large-scale omics data to develop mathematical and computational models for drug discovery primarily genetically engineered therapies.

Recent publications

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