Postdoctoral Fellow/Researcher in Computational Biology & Gene Regulation

The Computational Biology & Gene Regulation group led by Anthony Mathelier at the NCMM, a part of the Nordic EMBL Partnership for Molecular Medicine, is seeking an ambitious and highly motivated Postdoctoral Fellow or Researcher for a two-year position, starting as soon as possible in 2024. The selected candidate will play a pivotal role in a collaborative project spanning internationally renowned groups, namely those of Drs. Anshul Kundaje at Stanford University, USA, Wyeth Wasserman at the University of British Columbia, Canada, and Anthony Mathelier, NCMM, Norway. The position will be based in Norway. More information about the group can be found at https://mathelierlab.com/.

Join us to not only advance your career but also contribute to meaningful scientific discoveries and resources in the world of computational biology and gene regulation.

The selected candidate will contribute to a cutting-edge project aimed at enhancing and expanding computational resources to decipher transcription factor (TF) – DNA interactions. The focus will be on the enhancement of the JASPAR (https://jaspar.elixir.no) and UniBind (https://unibind.uio.no)  databases, which are officially recognized by ELIXIR Norway as Norwegian bioinformatics services. Specifically, the candidate will utilize advanced deep learning techniques to provide refined models and data crucial for the analysis of disease mutations affecting gene expression.

The candidate can refer to the following publications: https://doi.org/10.1093/nar/gkac1143, https://doi.org/10.1186/s12864-021-07760-6, https://doi.org/10.1038/s41588-021-00782-6, https://doi.org/10.1101/2022.12.20.520743, https://doi.org/10.48550/arXiv.1704.02685, https://doi.org/10.48550/arXiv.1811.00416.

The ideal candidate should meet the following criteria:

• Ph.D. in Computational Biology, Bioinformatics, or a related field.
• Proficiency in programming and experience with computational genomics data analysis.
• Experience in machine learning, particularly deep learning techniques.
• Experience in web development for scientific applications or databases; ideally proficiency in frameworks such as Django.
• Ability to collaborate with researchers from different fields and at different career stages.
• Willingness to be part of a team to share knowledge and skills.
• Documented ability to communicate science.
• Excellent written and verbal communication skills in English.

The following qualifications will count in the assessment of the applicants:

• Familiarity with TF-DNA interaction models and genomic interpretation tools would be a distinct advantage.
• Track record of developing reproducible computational pipelines, preferably with workflow management systems like Snakemake or Nextflow would be an advantage.
• Ability to containerize applications using Docker or Singularity for better software management and reproducibility.
• Prior experience with genomic databases, especially JASPAR or UniBind, is desirable.