ETH Zürich

Doctoral Student in High-throughput Analysis of Protein-Protein Interactions

📍 Basel

Role and responsibilities

Establish and validate a quantitative, high-throughput assay for measuring the mechanical stability of a protein-protein interaction relevant to blood clotting. Cross-validate high-throughput assay results against AFM measurements. Design and construct DNA variant libraries and display them on yeast. Apply next-generation DNA sequencing to quantify phenotypes. Develop computational pipelines to convert sequencing data into quantitative fitness values. Collaborate with a computational biology group at D-BSSE to develop and benchmark machine learning models. Prepare data and manuscripts for publication and present results at lab meetings and conferences. Enroll in and complete the requirements of the D-BSSE Doctoral program in Basel. Contribute to undergraduate teaching and practical supervision at the University of Basel.

Team / description

The Nash Lab (Lab for Engineering Synthetic Systems) is jointly affiliated with the Department of Chemistry at the University of Basel and the Department of Biosystems Science and Engineering of ETH Zurich (located in Basel). We work at the interface of protein engineering, molecular biophysics, and synthetic biology, developing new experimental and computational approaches to understand and engineer proteins for useful biomedical and industrial applications. Our research combines high-throughput screening, directed evolution, and single-molecule biophysical methods, and spans projects from fundamental protein science to translational applications.

Qualifications and Skills

  • A Master's degree in bioengineering, chemical engineering, biochemistry, molecular biology, biophysics, or a related field

  • A strong quantitative background and genuine interest in protein engineering, mechanobiology, and/or high-throughput experimental methods

  • Hands-on experience with molecular biology and protein expression techniques; prior exposure to yeast display, directed evolution, or single-molecule biophysics (e.g., AFM) is an advantage but not required

  • Comfort with, or willingness to learn, computational analysis of large sequencing datasets (Python or equivalent); experience with machine learning is a plus

  • Independent, careful experimental work combined with the ability to collaborate across two research groups and two institutions

  • Willingness to contribute to bachelor level teaching / chemistry practicals

  • Fluent written and spoken English

  • Eligibility for enrollment in the D-BSSE Doctoral program in Basel