Postdoc position in acid adaptation cancer bioinformatics University of Copenhagen, Denmark

Postdoc position in acid adaptation cancer bioinformatics

University of Copenhagen, Denmark

The Sandelin group is looking to recruit a talented postdoctoral researcher to our highly dynamic research group working in the interface of computational biology and medical genomics.

The position is for two years, available tentatively from Nov 1 2020, or soon as possible thereafter, in an interdisciplinary project focused on genetic and micro-environmental drivers of pancreatic cancer. Characteristic hallmarks of the disease are several specific driver mutations and a dense, acidic microenvironment. The interplay between these factors in driving disease onset and progression is uncharacterized. In this project, an interdisciplinary team will address this question using cell models, genomics and advanced bioinformatics approaches.

Research environment  
The project is a collaboration between Prof. Albin Sandelin, BRIC and Dept. of Biology, and Prof. Stine F. Pedersen, Dept. of Biology. The candidate will be based in Albin Sandelin’s group. The two groups are located within 5 minutes walking distance in the Northern Campus of the University of Copenhagen. Together, the groups employ several postdocs, PhD students, and undergraduate students and provide a strong, international research environment. The project will additionally be affiliated with the Marie Curie ITN project “pHIoniC”, in which two PhD students are already recruited for the project (one in each group).

The Sandelin laboratory is a joint wet and dry lab focusing on medical and fundamental transcriptomics (see Highlights from the lab include:

  • Anderson and Sandelin: Determinants of enhancer and promoter activities of regulatory elements. Nature Reviews Genetics 2019
  • Boyd et al: Characterization of the enhancer and promoter landscape of inflammatory bowel disease from human colon biopsies. Nature Communications 2018
  • Chen et al: Principles for RNA metabolism and alternative transcription initiation within closely spaced promoters. Nature Genetics 2016
  • Arner et al: Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells. Science 2015,
  • Andersson et al: An atlas of active enhancers across the human body. Nature 2014

Project and specific qualifications  
The candidate will be responsible for the computational analysis of CAGE data derived from cancer cell models, and integrating these data with phenotypic measurements at defined time points. Work with additional data including single cell RNA-seq, genotype data and RNA-seq data is expected.

Applicants must hold a PhD or equivalent in bioinformatics or a mathematical discipline with a strong biological interest, and a substantial publication record in high-quality international journals focused on the analysis of genomics data. Candidates finishing their PhD before Nov 2020 will also be considered.  We require:

  • Strong experience in analyzing high-throughput sequencing data, in particular CAGE and RNA-seq, including isoform analysis
  • Background in cancer bioinformatics, including survival analysis
  • Documented experience in statistical analyses of such data, including expression analysis, as well as quality control and visualization
  • Experience in statistical genetics and statistical modelling is a large advantage
  • Strong programming skills in Python and R, or equivalents, and experience using linux/unix platforms
  • Excellent English skills
  • One or more first authorships in well-respected bioinformatics or genomics journals
  • A passion for working in a highly interdisciplinary environment.

Experience in multivariate statistics, network and time course analysis and sequence analysis are strong advantages.  Although the focus will be on computational work, the candidate will be working closely together with experimental scientists, and will be expected to understand the experiments and underlying biology and fruitfully interact with other specialists.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Job description
The position is available for a 2-year period and your key tasks as a postdoc at SCIENCE are:

  • To manage and carry through your research project
  • Write scientific articles

Further information on the Department is linked at . Inquiries about the position can be made to Prof. Albin Sandelin ( ) or Prof. Stine F. Pedersen ( ).

Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

The starting salary is currently up to DKK 437.843 including annual supplement (+ pension up to DKK 74.871). Negotiation for salary supplement is possible.

The application, in English, must be submitted electronically by clicking APPLY NOW below.

Please include

  • Curriculum vitae
  • Diplomas (Master and PhD degree or equivalent)
  • Research plan – description of current and future research plans
  • Complete publication list
  • Separate reprints of 3 particularly relevant papers

The deadline for applications is 14 October 2020, 23:59 GMT +2. 

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.

You can read about the recruitment process at .


Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.

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