Doctoral Research Fellowship in Computational Biology & Gene Regulation
- Institution/Company:
- Computational Biology & Gene Regulation, Centre for Molecular Medicine Norway, University of Oslo
- Location:
- Oslo, Norway, Norway
- Job Type:
-
- PhD
- Degree Level Required:
- Masters
- Apply Now
Doctoral Research Fellowship in Computational Biology & Gene Regulation
A funded PhD candidate position is available in the Computational Biology & Gene Regulation group led by Anthony Mathelier at the Centre for Molecular Medicine Norway (NCMM), University of Oslo, Nordic EMBL partner for Molecular Medicine. See mathelierlab.com for further information. The position is part of the recently funded project “Cis-regulatory signatures for improved identification and stratification of breast cancer subtypes” selected through the Rosa sløyfe 2020 - Personalized breast cancer treatment call by the Norwegian Cancer Society (Kreftforeningen). The position will start in the first half of 2021 and is funded for three (3) years with possibility for extension.
Responsibilities:
The project aims at providing a map of active regulatory regions in breast cancer patients and developing machine-learning approaches to better stratify patients and identify breast cancer subtype cis-regulatory signatures. The selected candidate will specifically be involved in the implementation of a machine-learning approach to co-optimize the clusterization of patients and regulatory regions and will develop deep learning models to decipher the gene regulatory networks active in the identified cis-regulatory signatures. The developed methods will be applied to large experimental data sets publicly available as well as generated in house.
Qualifications:
We seek a highly motivated individual with documented experience with machine learning / deep learning models development ideally applied to high-throughput genomics data. We are looking for applicants excited about combining life sciences and computer science to analyze gene expression regulation. The successful candidate will be collaborative, independent, with strong enthusiasm for research, and should have experience in programming (mainly Python, R, and bash) dedicated to the analysis of large-scale genomics data. Being familiar with gene expression regulation in general, transcription factor binding, and the analysis of transcriptomics data (e.g. CAGE) analysis is an advantage. The position is open to applicants with a Master degree in computational biology/bioinformatics, computer science, or related fields. We offer a stimulating environment with excellent working and social benefits.
Qualification requirements:
- Master degree in computational biology, bioinformatics, biostatistics, or a related field
- Proficiency in programming (Python, R, bash)
- Documented experience with machine learning / deep learning method development
- 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
- Ability to communicate science
- Knowledge of eukaryotic gene expression regulation
- Knowledge of molecular biology
- Experience with analysis of genomics data sets
- High drive for science
- Proficiency in English
- Knowledge of CAGE (Cap Analysis of Gene Expression) data analysis is an advantage