IT:U is a new technical university in Austria (Linz) dedicated to digital transformation, driven by interdisciplinary research and project-based learning to actively shape this transformation and advance it with a solution-oriented approach.

Full-Time | Up to 4 years | On-site in Linz (AT) | Start Date: 1. April 2026 or later

Your tasks and responsibilities:

FIELD OF RESEARCH AND SCOPE:

Prof. Kristin Reiche, Professor of Digital Molecular Medicine, is looking for two Postdocs to join her research group to advance precision medicine by connecting biomedical data science, medical bioinformatics, (research) software engineering and advanced molecular diagnostic tools.

Her research group focuses on digital transformation in molecular medicine through research in:

• machine learning for (single-cell) multi-omics and spatial cell biology,
• patient-individual in silico models for risk and pathogenesis prediction,
• molecular biomarker discovery and validation, and
• software engineering and interoperability for medical bioinformatics.

Her research particularly targets advanced medical therapies like adoptive cellular immunotherapies, developing innovative digital solutions to understand their complex mechanisms of action aiming to advance personalized treatment strategies.

The postdoctoral researchers will be expected to contribute to the following areas:

• conducting research
• writing academic publications
• attending national and international conferences
• collaborating with other research groups on an interdisciplinary basis
• performing auxiliary activities in academic teaching for up to 2 weekly credit hours
• helping to file applications for third-party funding
• complying with the institution’s academic standards and ethical guidelines 

Your strengths and skills:

You must have completed a PhD degree (or an equivalent) in computer science, bioinformatics, (computational) biological sciences, mathematics, physics, or other relevant fields. 

Essential requirements:

• strong foundation in machine learning (ML) and biomedical data science
• proficiency in programming languages (Python, R) and ML/DL frameworks
• solid experience with Unix/Linux and Git version control
• core understanding of genetics, molecular biology, and immunology
• publication record in peer-reviewed scientific journals
• excellent communication and teamwork skills for interdisciplinary and international collaboration
• fluency in English (written and spoken)

Preferred qualifications:

• hands-on experience in single-cell multi-omics and/or spatial transcriptomics data analysis
• awareness of regulatory frameworks for medical bioinformatics and biomarker validation
• knowledge of virtual patient models or digital twin technologies

What you can expect:

Collaborations: 

• work with leading national and international research institutions
• participate in the EU-funded CERTAINTY project - A cellular immunotherapy virtual twin for personalised cancer treatment (https://www.certainty-virtualtwin.eu/)
• collaborate with our clinical partners in immuno-oncology and oncology 

International mobility and exchange:

• access to international research networks in precision medicine and medical bioinformatics
• opportunities to present research at leading international conferences
• potential research stays at international partner institutions

Professional and personal development:

• work in an innovative, interdisciplinary team at the intersection of data science, biomedicine, bioinformatics, molecular diagnostics and software engineering
• contribute to translational research with direct clinical impact
• develop and/or deepen your expertise in bioinformatics and machine learning for single-cell multi-omics, spatial transcriptomics, and biomarker development

Additional:

• innovative and stimulating working conditions in an interdisciplinary, international research environment

• office kitchen with complimentary basic supplies

• flexible working hours through a flextime model and the option for home office

• Free parking or Climate Ticket Upper Austria