Deep Learning Engineer for Urinary Tract Infections Detection

vor 1 Tag


Zürich, Zürich, Schweiz Eidgenössische Technische Hochschule Zürich Vollzeit

As a member of our dynamic and interdisciplinary research team at ETH Zurich, you will work on developing a novel diagnostic device using machine learning and data science approaches to identify volatile biomarkers associated with bacterial activity in urine samples.

The project focuses on distinguishing sterile from infected urine, predicting antimicrobial resistance profiles, and assessing the risk of invasiveness. You will leverage high-resolution volatilomics and machine learning to identify minimal combinations of volatile biomarkers that meet these objectives.

We are looking for a researcher with strong expertise in machine learning, deep learning frameworks, statistical modeling, and proficiency in Python programming. Experience with mass spectrometry data analysis or metabolomics and familiarity with microbial genomics, genetic manipulation, or metabolic pathway analysis are highly desirable.

  • Core Responsibilities:
  • Develop and implement machine learning models to analyze high-dimensional metabolomics data
  • Design and validate predictive algorithms for biomarker discovery
  • Collaborate with interdisciplinary teams, including clinical partners, engineers, and microbiologists
  • Prepare manuscripts, reports, and presentations to disseminate findings


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