PhD-Position (f/m/d)

The Institute of Pathology / LaBo[o]ratory of Nephropathology is offering a

to interrogate autoimmune kidney diseases using cutting-edge spatial transcriptomics and bioimage analysis techniques, including deep learning

Operational area: Institute of Pathology / LaBo[o]ratory of Nephropathology

Working hours: 75% of the collectively agreed full-time working hours (currently 38.5 hours per week)

Duration/Term of employment: Initially limited till 30.09.2029, with option of prolongation until the completion of the doctoral degree

Start date: as soon as possible

Remuneration/Rates: EG 13 (TV-L)

Project Title: Dissecting immune cell crosstalk in autoimmune kidney diseases with spatial transcriptomics and pathomics. Institute for Pathology, RWTH Aachen

Within this project the PhD candidate will interrogate immune cell crosstalk and crescent formation in patients with autoimmune kidney disease (including IgA nephropathy, ANCA-glomerulonephritis and others). The PhD candidate will learn to train and deploy histology segmentation models as part of the Aachen Digital Pathology group, as well as the downstream analysis of morphometric features in conjuncture with spatial transcriptomics.

This PhD-Program is meant to built a new generation of scientists that are rigorously trained in the development and application of cutting-edge computational tools to generate digital biomarkers with translational clinical impact. This combined skillset will enable the candidate to excel in their further academic or industry career after concluding the PhD training.

The PhD-Project is embedded within the section of Translational Nephropathology at the Institute of Pathology, offering a comprehensive training programs for PhD candidates, peer-to-peer mentoring, lectures and lab meetings on translational kidney research, as well as possibilities for networking and presentations at scientific meetings. We are an interdisciplinary and international team of scientists and clinicians with a long-standing focus and expertise in developing novel methods for digital pathology, advanced image analysis and deep learning. Our hardware equipment comprises high-end computational infrastructure, with several GPUs (NVIDIA DGX A100), CPU clusters and storage systems.

Tasks

• Development of a pathomics model for H&E- and PAS-stained histological slides of autoimmune kidney diseases

• Application and refinement of techniques for joint analysis of pathomics and spatial transcriptomics

• Implementation of biostatistical and machine learning models for predicting clinical outcomes using joint biomarkers

• Writing scientific publications and presentation of scientific data at medical conferences

Your profile

We are looking for a highly motivated and curious PhD candidate who is eager to learn and apply new computational methods, takes ownership of a project, and drives it forward with a structured, reliable working style. Strong communication skills in English (Lecel C1) and enthusiasm for interdisciplinary teamwork are highly valued.

• Applicants should have a master’s degree in biology, medicine, or a related field (e.g. engineering, molecular medicine, physics)
• Interested in working at the intersection of computational pathology and multi-omics. Ideally, applicants should have prior experience in either spatial transcriptomics or computer vision, ideally computational pathology approaches
• Development of a pathomics model for H&E- and PAS-stained histological slides of autoimmune kidney diseases
• Application and refinement of techniques for joint analysis of pathomics and spatial transcriptomics
• Implementation of biostatistical and machine learning models for predicting clinical outcomes using joint biomarkers
• Writing scientific publications and presentation of scientific data at medical conferences
• Motivation and eagerness to lean
• Ability to work indepedently / self-directed working
• Attention to detail
• Teamwork

Why you should choose us?

We offer…

• 30 days of vacation per year for full-time employment
• A bonus of 3,000 euros for employees who help recruit employees in different sectors
• An attractive company pension scheme from VBL
• Education opportunities, including updating and upgrading
• Access to public transport
• In-house kindergarten (places subject to availability)
• Staff residences (places subject to availability and by arrangement)
• An onboarding app for new employees
• Extended opening hours in the staff restaurant

Application:

The application deadline for the advertised position GB-P-56408 is October 16, 2026.

University Hospital of the RWTH Aachen, Institute of Pathology Section for Translational Nephropathology/AG Boor, Pauwelsstr. 30, 52074 Aachen.

Contact:

If you have any questions, please contact Univ.-Prof. Dr. med. Peter Boor PhD or Dr. med. David Hölscher

E-Mail: pboor@ukaachen.de / dhoelscher@ukaachen.de

Tel.: +49 (0) 241 80 35410

We look forward to receive your application.

This job advertisement is aimed at all genders.

The RWTH Aachen University Hospital promotes equal opportunity and diversity. Applications from women are expressly sought and, in accordance with relevant laws, will be treated preferentially.

We welcome applications from people with disabilities and they will be given priority if they are equally suitable.

Employment at a fraction less than the weekly full-time working hours stated above is generally possible.

It is preferable to use our digital application portal at www.karriere.ukaachen.de to apply. The portal allows you to upload your documents to an electronic application folder, which is protected from unauthorized access. Applications received by email are transferred to our application portal and then deleted in accordance with data protection regulations. (Transmission by email is usually inadequately protected.) If you do not agree to the transfer of your data to our portal, we unfortunately cannot consider your application. The data in the portal will be deleted after the retention period has expired.

This job advertisement was created using an AI-supported system. Final content review and responsibility lie with the Universitätsklinikum Aachen.

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