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Molecular Biology and Biophysics● OpenPreview

Doctoral Student in High-throughput Analysis of Protein Interactions

Develop high-throughput molecular assays and machine learning models for mechanobiology at ETH Zurich and the University of Basel.

Best for:Best for molecular biology and bioengineering graduates with a strong quantitative background and interest in machine learning and protein biophysics.

ETH Zürich · Basel, Switzerland · R1 · First-stage researcher
More professors at ETH Zürich
Protein engineeringMechanobiologyHigh-throughput screeningMachine learningBiophysics
Deadline
N/A
Funding
Salaried
Competitive salary in accordance with Swiss doctoral salary standards
Start date
flexible
Fixed-term
Location
Basel
Switzerland

Overview

This doctoral position is jointly hosted by the Nash Lab at the University of Basel and ETH Zurich's Department of Biosystems Science and Engineering. The candidate will design and validate high-throughput assays combining yeast surface display and deep sequencing to measure force-dependent protein interactions related to blood clotting. The research integrates experimental protein engineering with computational modeling in close partnership with a computational biology group. Responsibilities include building DNA variant libraries, analyzing high-throughput sequencing datasets, and training predictive machine learning models. The successful applicant will enroll in the D-BSSE doctoral program, contribute to undergraduate practical supervision, and prepare findings for publication.

PhDprotein-protein interactionsyeast displaydeep sequencingmolecular biophysicsETH ZurichUniversity of Basel

What you'll do

  • Establish and validate a quantitative, high-throughput assay to measure mechanical stability in blood clotting protein interactions
  • Cross-validate high-throughput screening results against atomic force microscopy measurements
  • Design and construct DNA variant libraries for yeast surface display
  • Apply next-generation sequencing to quantify experimental phenotypes
  • Develop computational pipelines to translate sequencing outputs into quantitative fitness values
  • Collaborate with computational biology partners to build and benchmark machine learning models
  • Draft scientific manuscripts and present research at international conferences and lab meetings
  • Complete the required coursework and milestones of the D-BSSE doctoral program
  • Assist with undergraduate practical supervision and teaching activities

Requirements

Degree required: Master's degree in bioengineering, chemical engineering, biochemistry, molecular biology, biophysics, or a related field

Degree offered: PhD

Language: English; fluent written and spoken proficiency

Instruction: English

Publications: None required, though publications or preprints can be included in the application if available.

Required skills
  • Strong quantitative background with a genuine interest in protein engineering or mechanobiology
  • Hands-on experience with molecular biology and protein expression techniques
  • Familiarity with computational analysis of large datasets using Python or equivalent languages
  • Ability to conduct independent experimental work and collaborate across multiple research institutions
  • Fluent written and spoken English proficiency
Nice to have
Prior exposure to yeast display, directed evolution, or single-molecule biophysics techniques like AFMExperience applying machine learning methods to biological datasets
Eligibility
  • Must hold an eligible Master's degree for enrollment in the D-BSSE doctoral program in Basel

Funding & terms

Type
Salaried
Amount
Competitive salary in accordance with Swiss doctoral salary standards
Duration
3-4 years
Programme
ETH Zürich
ETH Zürich

How to apply

Applicants must submit their complete application package exclusively through the online application portal. Email and postal submissions will not be reviewed.

Documents required
  • Cover letter
  • CV
  • Transcripts of all degrees
  • Master's thesis or representative project report
  • Publications or preprints
  • Reference contacts
↗Apply on site

Contact

MN
Prof.
Michael Nash
Department of Biosystems Science and Engineering
Lab
Nash Lab
ETH Zürich
Switzerland
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