The global SARS-CoV2 Pandemic has demonstrated the urgency to develop new tools for our arsenal against pathogens and human disease. If you are passionate about designing the next generation of genomic algorithms for host-pathogen interactions – we are looking for your talent!
Natural Language Processing has substantially improved deep learning on language and our understanding on linguistics due to unprecedented possibilities for text analysis. In a collaboration between the TU Dresden and CASUS we use transformer-based deep learning algorithms that treat genomes as text. The project will encompass the training of task-agnostic language models and use these to extract language rules and biological meaning, such as how genome stability is encoded in the genome.
The position will be mainly located in CASUS in Görlitz, Germany, embedded in the team of Artur Yakimovich and in close interaction with the group of Prof. Anna Poetsch at the Biotechnology Center of the TU Dresden, Germany.
Your tasks:
Kindly submit your completed application (including cover letter, CV, diplomas/transcripts, etc.) only via our Online-application-system:
https://www.hzdr.de/db/!BewerbungS1?pNid=490&pJid=1592&pLang=en