The University of Helsinki is one of the world’s leading universities for multidisciplinary research. The Helsinki Institute of Life Science HiLIFE is an independent research institute that supports high quality life science research across the University’s campuses and faculties. The Institute of Biotechnology BI, part of HiLIFE, is an internationally renowned research institute with an inclusive and curiosity-driven working culture. Research activities are carried out in research groups organised into three multidisciplinary research programmes. For further information please visit https://www.helsinki.fi/hilife/bi.

PROJECT SUMMARY

We are seeking a PhD student to join the project “Mutation clusters and origin of regulatory RNA genes” funded by the Jane and Aatos Erkko Foundation and led by Dr Heli Mönttinen at the Institute of Biotechnology, University of Helsinki.
In this project we aim to identify recent and ancient mutation events in human regulatory RNA gene regions and study their impact on gene function and structure using a range of sequence analysis and comparative genomic methods. The projects will also involve programming for data collection and analysis. As a PhD student, you will screen mutation events from large genomic datasets and analyse the effects of the identified mutations using existing software as well as well as newly developed computational methods. You are also be expected to report your results in a scientific publication as a first author with the help of other members of the group.

SKILLS, EXPERIENCE/QUALIFICATIONS

The successful candidate should have:

• Master’s degree in a relevant field (e.g. bioinformatics, genetics, molecular biology)
• Proven programming skills (preferably Python, other languages also appreciated)
• A strong background in biology
• Strong interest in molecular evolution
• Good written and oral communication skills (in English)
• Willingness to work both independently and as part of a team

We also appreciate:

• Good statistical skills
• Ability to handle large datasets
• Experience of working in HPC environments
• Previous experience in RNA and comparative genomics

Please refer the Job description for details