Ledig stilling på Universitetet i Oslo

Blindern og Urbygningen (Foto: Wikimedia og Colourbox)
Blindern og Urbygningen (Foto: Wikimedia og Colourbox)

Doctoral Research Fellowship in Computational Biology & Gene Regulation

Deadline> 22.01.2021

Universitetet i Oslo

The University of Oslo is Norway’s oldest and highest ranked educational and research institution, with 28 000 students and 7000 employees. With its broad range of academic disciplines and internationally recognised research communities, UiO is an important contributor to society.

Centre for Molecular Medicine Norway (NCMM) was established in 2008 and is the Norwegian node in the Nordic EMBL Partnership for Molecular Medicine. NCMM is a joint venture between the University of Oslo, Health Region South-East and the Research Council of Norway. From 2017 NCMM is merged with the Biotechnology Centre of Oslo and now has altogether 11 research groups. The overall objective of NCMM is to conduct cutting edge research in molecular medicine and biotechnology as well as facilitate translation of discoveries in basic medical research into clinical practice.

Job description

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.

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.

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

We offer

  • The PhD candidate position will be placed as SKO 1017 (position code) with salary NOK 482 200 – 535 200 per year depending on qualifications.
  • attractive welfare benefits and a generous pension agreement, in addition to Oslo’s family-friendly environment with its rich opportunities for culture and outdoor activities

How to apply

The application must include

  • Applicants should include (1) a cover letter outlining motivations, career goals, past achievements, and research interests, (2) a CV with list of publications, and (3) three referees contact information.

The application with attachments (pdf) must be delivered in our electronic recruiting system, please follow the link “apply for this job”. Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English.

Applicants may be called in for an interview.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

The appointment may be shortened/given a more limited scope within the framework of the applicable guidelines on account of any previous employment in academic positions.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.

Contact information

Inquiries about the position can be directed to Anthony Mathelier

About the application: Nina Modahl

Apply for position

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