The recent revolution in nucleic acid sequencing technologies, collectively referred to as "next-generation sequencing"(NGS), opened up unprecedented opportunities to discover novel viruses. It is becoming increasingly evident that the spectrum of currently known virus species just represents the tip of an iceberg. We developed and optimized a highly sensitive and specific method of viral sequence detection in unprocessed NGS data. By use of high performance computing we provided the proof of principle for the feasibility of our strategy in a recent study describing the discovery of a whole new family of non-enveloped fish viruses shedding light on the long-term coevolution of hepatitis B viruses with their vertebrate hosts over a period of 420 million years (Lauber et al., Cell Host & Microbe 2017). Due to the global medical importance, we will now put a major emphasis on the search for unknown human viruses in NGS data related to cancer, as well as some other specified diseases that might be linked to infectious agents, such as autoimmune and neuro-inflammatory disorders. We hypothesize that a substantial proportion of human viruses yet have escaped detection, particularly if they are transmitted vertically and/or cause only mild acute symptoms (if at all), while being able to establish latent long-term infections. Any such viruses could represent etiologic agents involved in the development of human disease without being so far recognized due to the temporal delay between primary infection and disease onset.

Your qualifications

Applicants should hold a Master degree in Bioinformatics or Biotechnology. We are looking for a highly motivated candidate with strong skills in scientific programming and expertise in handling and analyzing NGS data. Advanced knowledge in fundamental virology is advantageous. 

In addition:

Excellent academic performance

Very good master's degree in Bioinformatics or Biotechnology

Very good knowledge of English

Willingness to move to the university location

For further information:

 

https://hectorfellowacademy.applicationportal.org/home.html 

https://www.sciencedirect.com/science/article/pii/S1931312817303025?via%3Dihub