The Department of Biosystems Science and Engineering (D-BSSE) at ETH Zurich, in collaboration with Roche Pharma Research and Early Development (pRED), is offering a prestigious postdoctoral position as part of the Bio-Engineering Systems for Therapeutics (BEST) program under the Next-gen Bioengineers initiative. This interdisciplinary project is based in Basel and focuses on AAV capsid engineering using generative AI, with the goal of advancing gene therapy by overcoming current limitations in tissue tropism, immunity, and manufacturing yields.

The successful candidate will develop and implement state-of-the-art computational workflows for the design of novel AAV capsids, lead the computational design process, and participate in wet lab validation, including library construction, viral production, and NGS-based screening. The role also involves structural analysis using computational biology tools and the integration of high-throughput experimental data to refine generative models. The project is highly collaborative, offering dual supervision by Prof. Basile Wicky (ETH Zurich) and Dr. Denis Phichith (Roche), and provides access to world-class research infrastructure at both institutions.

Applicants must have a PhD in computational biology, bioinformatics, bio-ML, or a related quantitative field, with hands-on experience in generative models for proteins. A strong interdisciplinary drive, excellent communication skills in English, and a willingness to engage in both computational and experimental work are essential. The position is fully funded for two years, with comprehensive support for networking and career development.

To apply, candidates should submit a single PDF containing a motivation letter, CV, publication list, three recommendation letters, research statement, and doctoral certificate via the ETH Zurich online application portal. Applications are reviewed on a rolling basis. For further information, contact Prof. Basile Wicky or Dr. Denis Phichith. This opportunity is ideal for candidates passionate about bioengineering, computational biology, protein design, and translational medicine.