The aim of both the projects is to improve our understanding of mitochondrial physiology, in healthy and cancerous conditions, by utilizing advanced genomic and biochemical techniques, along with multi-omics integrative analyses. The projects will involve generating a substantial amount of NGS (Next-Generation Sequencing) and metabolomic data, including spatial transcriptomics data from in-vivo models.
The candidate will play an active role in developing and applying bioinformatic and computational biology methods for data processing and multi-omic integration, using network models.
We invite applications from highly motivated and outstanding students with a master’s degree or PhD in one of the following disciplines: Biology, Biotechnology or Statistics, Bioinformatics or Computational Biology. Students from related disciplines, such as Engineering, Physics or Mathematics are also welcomed to apply if motivated to biological applications. The candidate should have an appropriate problem-solving attitude, good communication skills, and be willing and able to work in team. Interest in molecular biology, cell biology and mitochondria mechanisms are expected. Additionally, the following skills would be an advantage for the selection:
- Experience in omic data analysis.
- Programming skills (R/Python).
- Ability to interact with scientists of different disciplines.