PhD scholarship in generative protein and peptide design for sustainable biomaterials - BRIGHT

BRIGHT; Kongens Lyngby; On-site; DKK 357,000 - 469,000; Full time

Job summary

BRIGHT at DTU invites applications for a PhD scholarship focused on generative protein and peptide design for sustainable biomaterials. You will design de novo proteins and peptides, using advanced diffusion and AlphaFold-inspired models, and integrate lab feedback to optimize synthesis and biosynthesis workflows.

You will collaborate with experimentalists to scale design-build-test-learn cycles and publish results in international venues, while mentoring MSc and BSc students.

Qualifications

• 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 English proficiency in written and oral form.
• Excellent communication and social skills for working within an interdisciplinary research team.
• Strong analytical skills and ability to work independently.

Responsibilities

• Generate de novo peptide and protein designs meeting multiple coupled property targets, including adhesion, cohesion, ion conduction and controlled degradability.
• Use and adapt generative molecular design tools such as RFdiffusion, ProteinMPNN and AlphaFold-type models.
• Develop and extend information-dense synthesis algorithms to manufacture designs in the laboratory.
• Extend these methods to expanded genetic codes, so that non-canonical residues can be encoded and biosynthesised rather than only chemically synthesised.
• Develop methods to learn from diverse measurements of material properties, via shared latent representations.
• Develop methods to continuously learn from iterative experimentation, by feeding back experimental data into an integrated model with quantified uncertainty.
• Work closely with experimentalists to optimize experimental designs for collecting high-information training data.
• Work closely with experimentalists to automate and scale up design-build-test-learn cycles.
• Report your research results in peer-reviewed scientific publications and international conferences.
• Collaborate within the research group and our local, national and international networks.
• Disseminate your results through public engagement and social media.
• Teach and supervise MSc and BSc students as well as research assistants

Skills

Python programming

English proficiency

Communication skills

Analytical skills

Independent work

Education

MSc in computational biology or related field

Tools

PyTorch

RFdiffusion

ProteinMPNN

AlphaFold

Job description

PhD scholarship in generative protein and peptide design for sustainable biomaterials - BRIGHT

This PhD project is part of a BRIGHT programme developing a general platform for the design of protein- and peptide-based biomaterials, with solid-state battery components as its first testbed. Our goal is to replace fluorinated PFAS polymers with de novo designed proteins and peptides.

You will generate the computational designs at the heart of the platform, by combining molecular foundation models with iterative laboratory feedback. You will develop design algorithms for biomaterials with natural and non-natural amino acids, and for planning their biosynthesis and biomanufacturing. You will develop lab-in-the-loop algorithms that use generative model-controlled stochastic synthesis to maximize information gain at every round of experimental testing.

Responsibilities and qualifications

• Generate de novo peptide and protein designs meeting multiple coupled property targets, including adhesion, cohesion, ion conduction and controlled degradability
• Use and adapt generative molecular design tools such as RFdiffusion, ProteinMPNN and AlphaFold-type models
• Develop and extend information-dense synthesis algorithms to manufacture designs in the laboratory
• Extend these methods to expanded genetic codes, so that non-canonical residues can be encoded and biosynthesised rather than only chemically synthesised
• Develop methods to learn from diverse measurements of material properties, via shared latent representations
• Develop methods to continuously learn from iterative experimentation, by feeding back experimental data into an integrated model with quantified uncertainty
• Work closely with experimentalists to optimize experimental designs for collecting high-information training data
• Work closely with experimentalists to automate and scale up design-build-test-learn cycles
• Report your research results in peer-reviewed scientific publications and international conferences
• Collaborate within the research group and our local, national and international networks
• Disseminate your results through public engagement and social media
• Teach and supervise MSc and BSc students as well as research assistants

Qualifications

• 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 English proficiency in written and oral form
• Excellent communication and social skills for working within an interdisciplinary research team
• Strong analytical skills and ability to work independently

Preferred qualifications but not mandatory

• Knowledge of protein structure and molecular biology
• Experience with protein design tools such as RFdiffusion, ProteinMPNN or AlphaFold
• Familiarity with DNA-encoded libraries, genetic code expansion or next-generation sequencing
• Interest in multi-objective optimisation, reinforcement learning, and bridging computational design with experimental realisation

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

We offer

DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. Please see DTU’s salary structure for scientific staff: www.inside.dtu.dk/en/human-resources/during-employment/salary/salary-structures

The starting date is 1 March 2027 (or according to mutual agreement). The position is a full-time position. The period of employment is 3 years.

You can read more about career paths at DTU here.

Further information

Further information may be obtained from Carlos Acevedo-Rocha: [e-mail]

You can read more about BRIGHT at https://bright.dtu.dk/

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU - Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar "PhD relocation to Denmark and startup "Zoom" seminar" for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

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.