Metabolomics Data Scientist - LC-MS Pipelines & Analytics Lead

DTU — Technical University of Denmark

København

On-site

DKK 650,000 - 900,000

Full time

8 days ago
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Job summary

The metabolomics data scientist will develop and maintain LC-MS-based metabolomics data and annotation pipelines, while supporting omics analyses and data infrastructure at the Department of Nutrition, Exercise and Sports, University of Copenhagen. You will contribute to training students and staff and collaborate across teams in an international environment.

We seek an experienced candidate with several years in metabolomics data analysis, strong programming skills in R and Shiny, and

Qualifications

  • PhD or at least 3 years in metabolomics or related discipline.
  • In-depth knowledge of LC-MS-based metabolomics analyses and annotation.
  • Experience developing or contributing to MS-based software.
  • Proficiency in R, Shiny, Linux and Docker.
  • Experience with data management and FAIR data principles.
  • Excellent communication skills in English.
  • Teaching experience in metabolomics is an advantage.
  • Wet-lab experience in metabolomics is an advantage.

Responsibilities

  • Develop and maintain LC-MS metabolomics data and annotation pipelines.
  • Maintain data infrastructure, SOPs and workflows; support omics analyses.
  • Collaborate with colleagues to ensure high-quality metabolomics data and results.
  • Train students and staff in metabolomics data analyses.

Skills

Metabolomics analysis
LC-MS pipelines
English communication
Academic teaching
Team collaboration

Education

PhD or 3+ years in metabolomics

Tools

R
Shiny
Docker
Linux

Job description

The metabolomics data scientist will develop and maintain LC-MS-based metabolomics data and annotation pipelines, while supporting omics analyses and data infrastructure at the Department of Nutrition, Exercise and Sports, University of Copenhagen. You will contribute to training students and staff and collaborate across teams in an international environment.

We seek an experienced candidate with several years in metabolomics data analysis, strong programming skills in R and Shiny, and

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