Junior Data Scientist - DTU Biosustain

We are looking for an enthusiastic data scientist for the Data Science platform to support our research groups. The job will include running data processing and analytics in collaboration with our DTU-Biosustain researchers and contributing to build our Informatics platform infrastructure.

The job
We are seeking a motivated Junior Data Scientist to join our Data Science Platform supporting biosustainability research. You will work closely with biologists and bioinformaticians developing sustainable solutions in areas such as microbial foods, natural products, and bio-based chemicals. This role is ideal for someone with a strong computational background who is eager to contribute and quickly learn in multi-omics analytics, microbial genomics, and AI-driven biological data science.

Your key responsibilities will be:

• Support data management, processing, curation, and analysis for biosustainability research projects.
• Perform data crunching and exploratory analyses across genomic, transcriptomic, proteomic, metabolomic, and other multi-omics datasets.
• Some experience running comparative genomics, metagenomics, and next-generation sequencing (NGS) analyses.
• Implement and maintain data workflows, preferably using Nextflow.
• Collaborate with platform data scientists and researchers to develop reproducible analytical pipelines.
• Assist in applying machine learning and AI methods to multi-omics datasets.
• Use version control (comfortable on the usage of Git/GitHub) for collaborative development and code maintenance.
• Eager to document processes, communicate analytical results, and contribute to best practices in data science and management.

Our expectations of you
Required skills and qualifications:

• Bachelor’s or Master’s degree in Bioinformatics, Computational Biology, Data Science, or a related field.
• Good level of Python and/or R.
• Hands-on experience with Git and GitHub for collaborative development.
• Familiarity with workflow management languages (e.g., Nextflow).
• Experience working with metagenomics, and NGS datasets.
• Basic understanding of machine learning approaches and AI-driven analyses in a biological context.

Preferred Qualifications

• Experience working with cloud computing environments (preferably Azure).
• Prior exposure to multi-omics integration or systems biology approaches.
• Interest in biosustainability, green transition research or related fields.

Soft Skills:

• Strong communicator
• Open-minded and collaborative
• Flexible and solution-oriented
• Committed, proactive, and eager to learn

What we offer in return
We offer an interesting and challenging job in an international atmosphere with the focus on research support, tooling development, teaching, innovation.

• Opportunity to contribute to impactful biosustainability research.
• Professional development and mentoring in data science and bioinformatics.
• Supportive, cross-disciplinary team environment.
• Exposure to state-of-the-art computational tools and cloud technologies.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations (AC). You are employed as an Academic Officer.

The position is a 20 hour appointment and permanent. Starting date is 1st January 2026.

The workplace is DTU Lyngby Campus. Exact address: Søltofts Plads, Building 220, 2800 Kgs. Lyngby

Application and contact
Please submit your online application no later than 16 December 2025. Open the “Apply now” link, fill out the form and attach your motivated application, CV and exam certificates. 

If you would like additional information about the position, please contact Alberto Palleja Caro (Team Lead at the Data Science Platform) on 20271069.

Applications 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. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

Data Science platform
The DSP team aims to make data science more accessible and inclusive at DTU Biosustain and across the DTU Community. The platform follows a data-centric approach that focuses on data infrastructure, processes, and outputs as ongoing, evolving products rather than one-time projects. Each data product is designed as a multidisc