
Computational Genomics Specialist in Molecular Medicine Research
4 days ago
About the Project
Human tumors are characterized by recurrent mutations in well-defined cancer driver genes, but also non-mutational epigenetic reprogramming and phenotypic plasticity controlled by transcription factors (TF) are important contributors to tumorigenesis. This project aims to utilize cutting-edge long-read nanopore sequencing combined with deep machine learning approaches to model the epigenetic changes and mutational mechanisms in cancers originating from endodermal tissues.
The goal is to reveal novel mechanistic details about the development of human cancer. The researcher will analyze NaNOME-seq, ATAC-seq, and RNA-seq data to identify novel epigenetic changes and mutational mechanisms.
Responsibilities
- Analyze large-scale genomic data sets to identify novel epigenetic changes and mutational mechanisms in cancers originating from endodermal tissues
- Use cutting-edge long-read nanopore sequencing combined with deep machine learning approaches to model the gene regulatory logic in epithelial cells
- Investigate the effects of DNA adducts on methylome, transcriptome, and gene regulatory logic
Requirements
- PhD degree in a relevant field
- Experience in computational genomics and machine learning
- Familiarity with long-read nanopore sequencing and deep machine learning approaches
- Strong publication record in a relevant field
- Good written and oral communication skills in English
Working Environment
The researcher will work closely with the Machine Learning in Biomedicine group and will spend short or long-term stays at the Precision Cancer Epigenomics lab, NCMM, University of Oslo, Norway, to conduct work required for the research project and foster synergies.
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