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Postdoctoral researcher for Clinical Omics Data Analysis at Technical University of Denmark (Copenhagen, Denmark)

Do you want to develop novel data science and machine learning approaches to aid clinically management of critically ill patients?

The CAG Center for Endotheliomics (CAG-CE) is seeking a highly motivated postdoctoral researcher in data science and machine learning to analyze clinical omics data in translational research focusing on endothelial cell metabolism in patients with critical illness such as trauma and severe infections.

CAG-CE is a clinical academic group (https://gchsp.dk/) involving six hospitals and two universities in the Copenhagen Region. The successful candidate will work closely with experimental and computational groups within the Novo Nordisk Foundation Center for Biosustainability (CFB), the computational groups at KU, and with physicians at Rigshospitalet.

You will join a dynamic team working on clinical and -omics data analysis, machine learning, software development, and next-generation sequencing data generation. Working at CFB, you have a unique opportunity to become equipped with cutting edge skills in statistical analysis, machine learning, mechanistic modeling and –omics data analysis, while our clinical collaborators provide an opportunity to work with international leaders in the study of endothelial cell phenotypes in patients with critical illness.

Develop and apply data science methods for CAG-CE
As the CAG-CE data scientist, you will be working on network/pathway-driven analysis of omics data obtained from critically ill patients and endothelial cell culture experiments. The data include metabolomics, proteomics, and genomics data along with typical patient metadata such as age, sex, health status, etc. You will be mining the Danish health registry and work with data hosted on cloud platforms such as Computerome.

More specifically, you mission is to develop and apply of data science methods (i.e. machine learning, statistical modeling) to integrate omics data in order to better predict therapeutic manipulation strategies.

PhD degree in engineering, bioinformatics, biology or similar field
We are looking for a colleague with 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).

Additionally, your CV will demonstrate experience in

  • omics data analysis, e.g., genomics, transcriptomics, proteomics, metabolomics, fluxomics;
  • developing scientific software in the current data science languages, including Python; and
  • using version control tools (i.e., git).

CAG-CE is an interdisciplinary, multinational team, so it is essential that you have good communication skills in English are essential.

Further information
If you would like additional information about the position, please contact Co-PI Igor Marín de Mas at igmar@biosustain.dtu.dk or Senior Researcher, Douglas McCloskey at domccl@biosustain.dtu.dk. If necessary, we will set up an additional phone call to ensure your understanding of the job and your many opportunities.

Salary and terms of employment
The period of employment is two years. 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.

Application procedure
Please submit your online application no later than 12 November 2020. Apply online at www.career.dtu.dk. Open the “Apply online” link, fill out the form and attach, in English as one PDF file, all materials to be given consideration including CV, cover letter, diploma and if relevant list of publications.

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

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

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