Bioinformatician (Msc) at Prinses Mxima Centrum
3584 Utrecht Oost, , Netherlands -
Full Time


Start Date

Immediate

Expiry Date

31 Aug, 25

Salary

5.289

Posted On

09 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Agile Project Management, R, Python, Linux, Java, Communication Skills, Cloud Computing, Data Science, Statistics, Genetics, Bioinformatics

Industry

Information Technology/IT

Description

The Big Data Core is looking for a highly motivated bioinformatician who excels in a stimulating, multi-disciplinary research environment and can help us build a federated pediatric oncology cloud.

EDUCATION AND SKILLS

We expect a highly motivated candidate with a bachelor or master in bioinformatics or similar experience in bioinformatics or data science. Excellent technical and programming skills are required, preferably in Linux, R, python and java. Knowledge about next-generation sequencing, genetics, statistics and large-scale computational infrastructures (including cloud computing) are also preferred. The candidate should also have good communication skills, be flexible, versatile and a good team player in a dynamic environment. The candidate should also be able to work in a structured manner with an attention to details and preferably have experience in software life cycle management and agile project management.

How To Apply:

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Responsibilities

The candidate will play a significant role in the data analysis as well as further development, implementation and integration of the genomics platform at the Princess Máxima Center. The candidate will work in close collaboration with bioinformaticians and laboratory specialists in both the Kemmeren group as well as other research groups in the institute.

Specific tasks include:

  • Operational analyses of WGS and RNA-seq data, as well as DNA methylation arrays.
  • Further development and implementation of the genomics platform using Nextflow or WDL/Cromwell, REST and large-scale computational infrastructures.
  • Support data resources and databases used for clinical data analysis.
  • Setting up and supporting bioinformatic analysis pipelines.
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