Institute for Medical Microbiology, Medical Virology and Hygiene, code 7903

Part-time:
65%

Limited:
30.11.2029* 1

Start of work:
December 1, 2026

Application deadline:
October 20, 2026

TV-L
idR E13 2

*extension possible

Tasks

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 generalizable 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

Benefits

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.

Modern Environment

innovative university hospital
state-of-the-art technology
world-class international research
excellent career prospects

Career & Development

structured onboarding
in-house academy
various training opportunities
targeted career development

Internationality

cultural & generational diversity
support through language courses
integration programs (nursing)

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 organizational 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). To view the latest work, please click here.

Contact us if you have any questions

Dr. Janko Sattler

07071 29-82351

Online application to

Mr. Dr. Janko Sattler
Index number: 7903
Including CV and cover letter
Application deadline: October 20, 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 wherever 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.

PhD Position - Machine Learning & Genomics in Antimicrobial Resistance Diagnostics

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