Postdoc: AAV capsid engineering with generative AI
ETH Zürich is well known for its excellent education, ground-breaking fundamental research and for implementing its results directly into practice.
Project background
Adeno-associated viruses (AAVs) are the leading platform for gene therapy, yet their clinical potential is often capped by sub-optimal tissue tropism, pre-existing human immunity, and low manufacturing yields. This project aims to develop and deploy state-of-the-art generative models in protein design for improving AAV manufacturing properties.
Responsibilities
Generative modeling: develop and implement state-of-the-art computational workflows to design novel AAV capsids
Dry-to-wet: lead the computational design process and actively participate in wet lab validation of your designs (e.g., library construction, viral production, NGS-based screening)
Structural analysis: utilize computational structural biology tools to ensure designs maintain assembly competence and structural integrity
Data integration: process and analyze high-throughput experimental data to iteratively refine generative models
Collaboration: work at both Roche pRED and ETH Zurich D-BSSE (both located in Basel) to translate AI-driven designs into improved AAV vectors
Profile
PhD degree or equivalent in computational biology, bioinformatics, bio-ML, or a related quantitative field (required)
Hybrid mindset: you are deeply interested in applying computational biology to solving translational challenges; AAV experience is welcome but not necessary
Generative AI: hands-on experience with modern generative models for proteins (required)
Interdisciplinary drive: high motivation to work at the intersection between wet and dry lab work, with a willingness to be trained in experimental validation techniques
Communication: excellent oral and written communication skills in English, with the ability to bridge the gap between ML concepts and experimental molecular biology
We offer
End-to-end research ownership: the unique opportunity to own the entire process; from in silico design to experimental validation
Innovation: an exciting and highly collaborative research environment between academia (ETH) and industry (Roche)
Mentorship: dual supervision by ETH Zurich and Roche principal investigators
Infrastructure: full access to world-class facilities at both the Roche and ETH Zurich campuses in Basel
Development: a fully funded 2-year fellowship including dedicated support for networking and career development
In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.
Curious? So are we.
We look forward to receiving your online application with the following documents as a single PDF:
A letter of motivation (max 1 page).
CV (max 2 pages).
Full list of publications.
3 letters of recommendation.
Brief statement of research interests (max 1 page).
Copy of your original doctoral degree certificate if already obtained.
The position will be filled on a rolling basis.
We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Job details
Title: Postdoc: AAV capsid engineering with generative AI
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