The world is changing at an ever-faster pace. At the Johannes Kepler University Linz, we work on technologies and the ideas of tomorrow on a daily basis. At the same time, we educate over 27,000 young people to meet the demands of today’s job market. In short, we are Upper Austria’s largest institution for education and research. Are you interested in being a part of shaping the future of Austria’s most attractive campus university? We currently have a job opening for a:

Graduate Project Assistant (must hold a Diploma/Master’s degree) for a 30-hour/week (part-time), three-year position

Organizational unit::

Klinisches Institut für Pathologie und Molekularpathologie

Entry date::

01/07/2027

Job Reference Number::

60900-2026-002133

:

Our research project “Analysis of response to Immunotherapy in MSI tumors: Evaluation and Prediction of Response to Immunotherapy in Microsatellite Instable Carcinomas” investigates molecular and cellular heterogeneity using state-of-the-art multi-omics, spatial transcriptomics, and computational pathology to gain insights into tumor biology, therapy resistance, and biomarker development. The project is conducted by an interdisciplinary and international team of pathologists, molecular biologists, and computational pathology experts, providing an innovative environment for translational cancer research.

We are seeking a PhD candidate with advanced programming and computational expertise to lead data analysis, integration, and methods development. This role complements our existing team of highly skilled molecular biologists and laboratory technicians and centers on computational pathology, spatial omics analytics, and bioinformatics for large, complex datasets.

Job Duties::

Develop and maintain robust bioinformatics and biostatistics pipelines for spatial transcriptomics and multiplex spatial phenotyping, in collaboration with LIMICS, the Sorbonne Center for AI, and SIRIC CURAMUS hubs in Paris
Integrate and analyze RNA, protein, and whole-slide imaging data; perform quality control, normalization, cell/tissue-level annotation, and advanced visualization of new data types arising from spatial technologies
Lead machine learning and deep learning approaches for digital pathology, including segmentation, phenotyping, and feature engineering from segmented tissue compartments; extend existing classifiers and analysis pipelines (e.g., QuPath-based workflows)
Apply in-situ multi-omics platforms (data side); collaborate with wet-lab colleagues for experimental design and data readiness
Manage high-performance computing workflows for whole-slide images and large spatial datasets; use GPU-accelerated methods as required by ML/DL pipelines
Collaborate within an international network with annual on-site meetings (Linz/Paris), weekly virtual lab meetings, and a planned several-month research stay in Paris to deepen in-situ transcriptomics, bioinformatics, and statistics skills
Document and present results in internal meetings, conferences, and publications; contribute to teaching and co-supervision of students
Established digital pathology pipelines (e.g., QuPath, python) for multiplex immunofluorescence, segmentation, phenotyping, and spatial neighborhood analyses; machine learning classifiers for tissue compartmentalization already in development
International collaboration with Sorbonne University teams (CRSA, SIRIC CURAMUS) and dedicated support for bioinformatics/AI pipeline setup and integration
Close collaboration with the Clinical Research Institute Medical Artificial Intelligence
Conducting independent scientific research within the framework of the project with the aim of completing a doctoral thesis (PhD thesis)

Your Qualifications::

The successful candidate must hold a completed diploma or master’s degree in computer science, life sciences, medicine, or related fields (or closely aligned computational fields with a strong interest in biomedical applications)
Strong programming skills and computational expertise aligned with bioinformatics, statistics, and computational pathology for spatial omics and digital pathology data processing
Experience with machine learning/deep learning for image analysis and/or omics integration; familiarity with pipeline development and GPU-accelerated computing is an advantage
Ability to collaborate with interdisciplinary teams and to communicate effectively in English; German B1 or willingness to learn German is expected (English B2)
Independent, reliable, and team-oriented working style

What We Offer::

On the basis of full-time employment (40 hours/week) the minimum salary in accordance with the collective agreement is € 3,776.10 gross per month (14 x per year, CA Job Grade: B1)
Stable employer
Attractive campus environment with good public transportation connections
Attractive continual educational opportunities
State-of-the-art research infrastructure
Dynamic research environment
Exercise and sports classes (USI)
…and much more

Application due date::

11/16/2026

:

The Johannes Kepler University wishes to increase the proportion of academic female faculty and, for this reason, especially welcomes applications by qualified women. If applicants are equally qualified, a woman will be given preference for this position. The university welcomes applications from qualified applicants with disabilities. These applications will be given special consideration.

Space for your future? We look forward to receiving your application via our job portal. For further information, please contact: Univ. Prof. Dr. Rupert Langer, E-mail: rupert.langer@kepleruniklinikum.at.

Location::

Krankenhausstraße 5, 4020 Linz