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Postdoc in Computational Biology at Technical University of Denmark (Copenhagen, Denmark)

Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain) at the Technical University of Denmark (DTU) and the SHINE Group at Rigshospitalet, Copenhagen University Hospital are seeking a highly motivated postdoctoral researcher in genome-scale biochemical network modeling and omics data analysis for translational research focusing on endothelial cell metabolism in patients with critical illness such as trauma and severe infections.

The successful candidate will join a dynamic team working on data analysis, predictive modeling, software development, and next-generation sequencing data generation related to the ENDOTHELIOMIC research project. Research will be conducted in collaboration between the CFB and SHINE Group at Righospitalet:  DTU Biosustain will provide an unique opportunity to become equipped with cutting edge skills in metabolic modeling and –omics data analysis, while the SHINE group will provide the opportunity to work with international leaders in the study of endothelial cell phenotypes in patients with critical illness.

The position will require working closely with experimental and computational groups within DTU Biosustain and with physicians in the SHINE Group at Rigshospitalet.

Responsibilities and tasks

  • Network/pathway-driven analysis of omics data obtained from critically ill patients and endothelial cell culture experiments. Specifically, the applicant will be working with metabolomics, proteomics, and genomics data along with typical patient metadata such as age, sex, health status, etc
  • Assessment, application, and development of methods for integration of omics data with modeling in order to predict therapeutic manipulation strategies. Specifically, the applicant will be expected to develop both constraint-based and kinetic models using the omics data.
  • The applicant will need to mine the Danish registry and work with data hosted on cloud platforms such as Computerome.


  • Candidates should hold a PhD degree in engineering, bioinformatics, biology or similar field
  • The applicant should have previous experience in using bioinformatics, statistics, and machine learning to answer biological questions. This includes familiarity with common visualization modules (e.g., in matplotlib in python) and statistics and machine learning modules (e.g., TensorFlow, scikit-learn, etc. in python)
  • Previous experience in constraint-based modeling and kinetic modeling is desirable
  • Experience in omics data analysis (for example genomics, transcriptomics, proteomics, metabolomics, fluxomics) is required
  • Previous experience in developing scientific software in Python or similar language using version control tools (i.e., git) is required
  • Good communication skills in English are required

We offer
We offer an interesting and challenging job in an international environment focusing on education, research, and innovation, which contribute improved patient outcome and improving social welfare. We strive for academic excellence, collegial respect and freedom tempered by responsibility.

Salary and terms of employment
Researcher salaries and benefits in Denmark are competitive world-wide.

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.

You can read more about career paths at DTU here.

The place of work is in Lyngby (DTU) and Copenhagen (Rigshospitalet).

The period of employment is 2 years.

Further information
Further information may be obtained from:

Application procedure
Please submit your online application no later than 27 December 2019 (local time).

Apply at

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • Application (cover letter)
  • CV
  • Diploma (MSc/PhD)
  • List of publications

 Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.