PhD Position - Machine Learning & Genomics in Antimicrobial Resistance Diagnostics

Universitätsklinikum Tübingen; Tübingen; Vor Ort; EUR 42.000 - 56.000; Vollzeit

Benefits dieser Stelle

Good public transport connections

Parking space sharing & ride-sharing

Canteen discounts

Job bike & corporate benefits

Zusammenfassung

Universitätsklinikum Tübingen offers a PhD position in Machine Learning and Genomics focused on antimicrobial resistance diagnostics. You will join a newly established research group at the interface of medical microbiology, bacterial genomics, and machine learning, with close supervision and scope to shape your research environment.

The role combines computational analysis with bench experiments and provides opportunities to participate in national and international consortia, with potential

Qualifikationen

• Master's degree in bioinformatics, microbiology, or a comparable subject.
• Confident programming in Python and experience with Linux-based bioinformatics tools.
• Practical experience with machine learning and/or whole-genome sequencing data analysis.

Aufgaben

• Develop and clinically evaluate ML models for detection of resistance plasmids from MALDI-TOF spectra.
• Perform genomic analysis of carbapenemase-producing Enterobacterales and their mobile elements using short- and long-read sequencing.
• Establish and analyze linked MALDI-TOF and genome datasets for predictive models.
• Experimentally validate computational predictions with bench work and collaborations.
• Contribute to national and international consortia and present results at conferences/journals.

Kenntnisse

Python programming

Linux environment

ML experience

Genomics data analysis

Ausbildung

Master's degree in bioinformatics or microbiology

Jobbeschreibung

PhD Position - Machine Learning & Genomics in Antimicrobial Resistance Diagnostics (f/m/d)

Institute for Medical Microbiology, Medical Virology and Hygiene, Kennz. 7903

• Development and clinical evaluation of machine-learning models for the detection of resistance plasmids directly from routine MALDI-TOF mass spectra
• Genomic analysis of carbapenemase-producing Enterobacterales and their mobile genetic elements, using short- and long-read whole genome sequencing
• Establishment and analysis of linked MALDI-TOF and genome datasets as the basis for generalisable predictive models
• Experimental validation of computational predictions through conjugation, plasmid curing and stability assays, supported by a dedicated technical assistant
• Contribution to national and international consortia (DZIF TTU-HAI, ESGEM-AMR) and presentation of results at conferences and in peer-reviewed journals

Profile

• Completed Master's degree in bioinformatics, microbiology, or a comparable subject
• Confident programming in Python and experience working in a Linux environment with bioinformatics tools
• Practical experience with machine learning and/or analysis of whole-genome sequencing data
• Interest in bacterial genomics and clinical microbiology and willingness to combine computational work with experiments at the bench
• Independent and structured working style, team orientation and scientific rigour, ideally evidenced by a first publication

You will join a newly established research group as one of its first members, with close supervision, technical support, and scope to shape your research environment, while benefiting from regular exchange with CMFI and participation in IGIM.

• innovative university hospital
• state-of-the-art technology
• world‑class international research
• excellent career prospects
• structured onboarding
• in‑house academy
• diverse training opportunities

Internationality

• cultural & generational diversity
• support through language courses

Research

• cutting‑edge research at the highest level
• support from PhD to professorship

Mobility & offers

• good public transport connections
• parking space sharing & ride‑sharing service
• discounts in the canteen & cafeteria
• job bike & other corporate benefits

About us

The Faculty of Medicine is one of the four founding faculties of the Eberhard Karls University of Tübingen. With its non‑clinical facilities as well as its research and teaching area corresponding to the organisational units of the University Hospital, it is one of the largest medical training and research institutions in Baden-Württemberg.

About the research group

Newly established research group at the interface of medical microbiology, bacterial genomics and machine learning (AG Sattler). We develop data‑driven approaches to antimicrobial resistance diagnostics and investigate the genomic epidemiology of multidrug‑resistant bacteria, combining computational analysis with experimental validation. The position offers the opportunity to obtain a doctoral degree (Dr. rer. nat.) and is embedded in national and international research consortia (DZIF, ESGEM-AMR).

Application deadline: 06.10.2026

We offer remuneration in accordance with TV-L (collective wage agreement for the Public Service of the German Federal States),severely handicapped persons with equal qualifications are given preferential consideration.Interview expenses are not covered.Please note the applicable vaccination regulations.The employer actively promotes equal opportunities and particularly encourages applications from women.

1 Continued employment will be sought whereever possible.

2 The data provided does not constitute a basis for an employment contract at the University Hospital of Tübingen. It is intended to serve as a rough guide for all interested parties. Remuneration is governed by the applicable collective bargaining agreements in conjunction with the corresponding pay scales. Further information can be found here .