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Technical University of Denmark

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PhD scholarship in generative protein and peptide design for sustainable biomaterials - BRIGHT Technical University of Denmark in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

PhD scholarship; salary and appointment terms follow the collective agreement with the Danish Confederation of Professional Associations. The position is full-time for 3 years.

Deadline

Dec 6, 2026

Country flag

Country

Denmark

University

Technical University of Denmark

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Keywords

Computer Science
Chemical Engineering
Materials Science
Deep Learning
Biology
Synthetic Biology
Protein Engineering
Biomanufacturing
Biomaterials
ML

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About this position

This PhD project sits within BRIGHT, a mission-oriented research programme at the Technical University of Denmark focused on creating PFAS-free biomaterials through biotechnology. The work aims to build a general platform for designing protein- and peptide-based biomaterials, with solid-state battery components as the first testbed.

The core research challenge is to replace fluorinated polymers with de novo designed proteins and peptides. The PhD researcher will generate the computational designs at the heart of the platform by combining molecular foundation models with iterative laboratory feedback. The project also develops design algorithms for biomaterials containing natural and non-natural amino acids, together with methods for planning biosynthesis and biomanufacturing.

A major part of the work is to create lab-in-the-loop algorithms that use generative model-controlled stochastic synthesis to maximize information gain at each experimental round. The project spans design-build-test-learn cycles, with a strong emphasis on shared latent representations, quantified uncertainty, and continuous learning from experimental data.

The research agenda includes generating peptide and protein designs with coupled property targets such as adhesion, cohesion, ion conduction, and controlled degradability; adapting state-of-the-art tools such as RFdiffusion, ProteinMPNN, and AlphaFold-type models; and extending methods to expanded genetic codes so that non-canonical residues can be biosynthesised. The wider BRIGHT Mission 1A framework connects AI-guided protein and peptide design with microbial engineering, cell-free prototyping, fermentation, purification, and material characterization.

The position is embedded in an international, interdisciplinary environment at DTU, with close collaboration with experimentalists and networks across academia and industry. The listed contact person is Carlos Acevedo-Rocha.

Funding details

PhD scholarship; salary and appointment terms follow the collective agreement with the Danish Confederation of Professional Associations. The position is full-time for 3 years.

What's required

Applicants must have a two-year master's degree (120 ECTS points) or an equivalent degree at the same academic level. Required background includes an MSc in computational biology, bioinformatics, biophysics, computer science or a related area, programming experience in Python, experience with deep learning frameworks such as PyTorch, excellent written and spoken English, excellent communication and social skills for interdisciplinary teamwork, strong analytical skills, and the ability to work independently. Preferred but not mandatory are knowledge of protein structure and molecular biology, experience with RFdiffusion, ProteinMPNN or AlphaFold, familiarity with DNA-encoded libraries, genetic code expansion or next-generation sequencing, and interest in multi-objective optimisation, reinforcement learning, and bridging computational design with experimental realisation.

How to apply

Submit the complete online application by the deadline through the Apply now link. Upload one PDF in English containing a motivation letter, CV, grade transcripts, BSc/MSc diploma with grading scale, and one recommendation letter with the referee’s email and phone number. You may apply before receiving the master’s degree, but you must have it before starting.

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