100%, Basel, fixed-term

100%, Basel, fixed-term

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.

Project background

Many proteins in the human body experience shear stress and other types of mechanical force, and this is believed to play a central role in their activity. Yet we still lack high-throughput techniques to measure how proteins respond to mechanical force. This project will develop high-throughput methods involving molecular surface display and deep sequencing to study force-dependent behavior in protein systems. These datasets will, in turn, be used to train machine learning models capable of predicting mechanical behaviors of molecular and cellular systems.

As a proof of concept, we will apply this platform to study interactions central to blood clotting, with direct relevance to Von Willebrand disease, a common bleeding disorder. The Doctoral Student will work at the interface of protein engineering, single-molecule biophysics, and machine learning, in close collaboration with a computational biology group (Beerenwinkel) at D-BSSE. The project offers hands-on training across the full pipeline, from high-throughput experimental design to predictive modeling, and the resulting methods and datasets are intended to serve as an open resource for the broader research community.

Job description

• 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

Profile

• 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

Workplace

Workplace

We offer

• A Doctoral Position with primary supervision by Prof. Michael Nash and co-supervision by Prof. Niko Beerenwinkel, combining experimental and computational work
• Enrollment in the D-BSSE Doctoral program, with access to its coursework, seminar series, and interdisciplinary training environment
• A well-equipped lab at Mattenstrasse 22, 4058 Basel with established protein expression, yeast display, AFM, and high-throughput infrastructure, plus support from lab senior scientific and technical staff
• Close mentorship from a PI with an established track record in protein engineering and single-molecule biophysics, and collaboration with a leading computational biology group
• Funding to attend international conferences and present your work
• An international and interdisciplinary team of energetics Doctoral Students, postdocs and scientists
• Exposure to ongoing projects in technology commercialization
• A collaborative, interdisciplinary project spanning molecular engineering, mechanobiology, high-throughput screening, and machine learning, with direct relevance to a clinical medicine
• Competitive salary in accordance with Swiss doctoral salary standards

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Curious? So are we.

We look forward to receiving your online application with the following documents:

• Cover letter addressed to Prof. Michael Nash, describing what you have achieved thus far, which direction you want to work in, and why (one to two pages)
• Detailed CV, including a list of any publications or preprints
• Transcripts of all degrees in English, with the local grading scale, which ETH requires for doctoral admission
• Your Master's thesis or a representative project report, in English. A draft or an in-progress version is fine if you have not finished yet
• Up to two of your publications or preprints, if you have them. We do not expect publications at this stage, but if you have written something we would like to read it
• Names and contact information of at least two references, usually your thesis supervisor (Reference letters are optional)

Further information about the lab can be found on our Website . Questions regarding the position should be directed to Michael Nash, [email protected] (no applications).

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.