A fully funded PhD scholarship is available in machine learning–driven enzyme and process engineering as part of the Horizon Europe MSCA Doctoral Network ELEGANCE. The project is hosted at the Computational Protein Engineering (CPE) group at DTU Biosustain.
The position focuses on advancing computational and experimental strategies for engineering enzymes with improved activity, selectivity, stability and bioprocess performance.
Project Focus
- Engineering monooxygenases for enhanced activity, selectivity and stability.
- Developing strains for high-throughput screening of large enzyme libraries.
- Establishing analytical workflows (HPLC, LC-MS, GC-MS).
- Protein expression, purification and biophysical/biochemical characterization.
- Variant identification using next-generation sequencing.
- Applying machine learning–guided directed evolution.
- Upscaling selected biotransformation reactions with academic partners.
Responsibilities
- Integrate enzyme engineering, process engineering and machine learning.
- Participate in training events, workshops and secondments within the ELEGANCE network.
- Collaborate within CPE and international research partners.
- Publish in peer-reviewed journals and present at international conferences.
- Contribute to teaching and supervision activities.
Qualifications
- MSc in biotechnology, biochemistry, biology, chemistry, biophysics or related field.
- Experience in molecular biology and protein engineering.
- Experience with enzyme assays and kinetics.
- Strong English communication skills and ability to work independently.
Preferred (not required):
- Bioinformatics and NGS experience.
- Automation and coding (Python or similar).
- Experience with AlphaFold, PyMOL, Chimera or related tools.
- Interest in machine learning and computational protein design.
Additional Information
The position is fully funded under MSCA conditions and follows DTU’s PhD regulations. Salary is based on the Marie Curie compensation scheme.
Application Deadline
31 January 2026 (23:59 Danish time)
Applications must be submitted as a single PDF including: cover letter, CV, transcripts, and diplomas.
Further details and application link are available through the official DTU portal.