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DTU Bioengineering

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Postdoc in environment-responsive antibody and nanobody discovery at DTU Bioengineering DTU Bioengineering in Denmark

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Aug 31, 2026

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Country

Denmark

University

DTU Bioengineering

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Keywords

Computer Science
Biomedical Engineering
Chemical Engineering
Deep Learning
Biology
Computational Biology
Antibody Engineering
Protein Engineering
Toxinology
Generative Modeling
Protein-protein Interaction
Statistics
bio engineering

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About this position

DTU Bioengineering in Kgs. Lyngby, Denmark is advertising a 4-year postdoc in environment-responsive antibody and nanobody discovery within the Antibody Technologies Group, led by Professor & Head of Section Andreas Hougaard Laustsen-Kiel.

The project, PROTÆCT (Precision Regulation Of Toxin Activity through Environmentally-Controlled Targeting), is funded by the Villum Foundation and focuses on designing binding proteins whose activity changes with environmental cues such as pH and metal ions. The work sits at the interface of protein engineering, toxin biology, computational biology, and deep learning.

The successful candidate will design, discover, and characterize antibodies, nanobodies, and other binding proteins with condition-dependent activity. The role combines in silico design, generative models, representation learning, and experimental collaboration with wet-lab scientists who will express and test the designs. Potential applications include targeted therapeutics, biosensing, synthetic biology, and control of protein function in complex biological environments.

Key responsibilities include developing deep learning architectures for protein generation, optimizing de novo binder design models, linking computational predictions to experimental data, publishing in strong journals, contributing to grant applications, and mentoring PhD/MSc/BSc students. The group works closely with international collaborators, especially the University of Porto and the Scripps Research Institute.

Eligibility highlights: applicants must hold a PhD (or equivalent) in Computer Science, Machine Learning, Artificial Intelligence, Computational Biology, or a closely related field. Strong experience with Python, PyTorch and/or JAX, large-scale neural networks on HPC/GPU clusters, and sequence/structural modeling is required. Experience with protein language models, antibody-specific language models, structure prediction, geometric deep learning, graph neural networks, molecular modeling, or MLOps is an advantage.

Application deadline: 31 August 2026, 23:59 Danish time. Apply online and submit one PDF containing a cover letter, CV, academic diplomas (MSc/PhD), and publication list.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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