⛔ This position is no longer available.
University: Medical University of Vienna
Country: Austria
Deadline: 2026-06-03
Fields: Computer Science, Bioinformatics, Applied Mathematics, Physics, Biomedical Engineering
Are you passionate about leveraging artificial intelligence and advanced machine learning to revolutionize biomedicine and healthcare? If you are seeking a research environment where you can contribute to the next generation of AI-driven discoveries in medicine, the Medical University of Vienna offers an exceptional opportunity for your academic and professional growth.
About the University or Research Institute
The Medical University of Vienna stands as one of Europe’s most prestigious medical institutions, renowned for its tradition of excellence in research, teaching, and clinical care. Located in Austria’s vibrant capital, Vienna, the university is deeply embedded in a city celebrated for its rich history, cultural diversity, and high quality of life. The Medical University of Vienna is internationally recognized for its pioneering contributions to biomedical research and innovation, attracting scholars and scientists from around the world. Its collaborative academic environment fosters interdisciplinary research, supported by state-of-the-art facilities and a strong network of clinical and industrial partners.
Austria itself is a hub for scientific advancement in Europe, offering a high standard of living, excellent healthcare, and a welcoming multicultural atmosphere. International students benefit from a supportive research community, attractive funding opportunities, and access to world-class resources.
Research Topic and Significance
This PhD position centers on the development of novel machine learning models tailored for complex, multimodal biomedical data. With the rapid expansion of high-dimensional datasets in modern medicine—such as single-cell and spatial omics, histology, and biomedical imaging—there is a critical need for scalable and interpretable AI models that can derive meaningful biological insights and support translational applications.
The research is housed within the Center for AI in Medicine (CAIM) and the MetAGE Cluster of Excellence, both at the forefront of integrating artificial intelligence with medical research. By advancing generative and mechanistic approaches in machine learning, this project aims to bridge the gap between computational innovation and real-world biomedical challenges. The outcomes have the potential to transform diagnostics, treatment planning, and our fundamental understanding of complex biological systems.
Project Details
Successful candidates will join a dynamic research team at the Department of Internal Medicine III, collaborating closely with experimental and clinical partners. The position offers a full-time, four-year contract with the possibility of extension, commencing on 1 September 2026 or shortly thereafter. Key responsibilities include:
– Conducting independent research towards a doctoral dissertation.
– Developing and implementing computational pipelines for large-scale biomedical datasets.
– Engaging in interdisciplinary projects with both experimental and clinical teams.
– Contributing to high-impact scientific publications and conference presentations.
– Participating in teaching, examinations, and supervision of junior students.
– Building reproducible and scalable AI models with a focus on biological interpretability.
This position is advertised by Professor Stathis Megas via LinkedIn. For more information and details on how to apply, please consult the official LinkedIn post:
https://www.linkedin.com/posts/stathis-megas-87530294_ai-machinelearning-phd-share-7460957042338512896-rJFz
Candidate Profile
Ideal applicants will have a strong academic background and a passion for interdisciplinary research at the intersection of AI and biomedicine. The following qualifications are sought:
– A Master’s degree (or equivalent) in computer science, bioinformatics, applied mathematics, physics, or a closely related discipline.
– Advanced programming skills, particularly in Python.
– Experience with machine learning frameworks such as PyTorch or JAX.
– Solid grounding in machine learning, statistics, and analytical thinking.
– Demonstrated interest in working with large-scale biomedical datasets.
– Familiarity with generative models, probabilistic modeling, graph-based methods, or GPU-based computing is highly desirable.
– An aptitude for collaborative work across experimental and clinical domains.
Candidates with experience in single-cell or spatial omics, biomedical imaging, or computational biology will find this position particularly well-suited to their interests and expertise.
Application Process
Application Deadline: 2026-06-03
To apply, candidates should prepare a complete application package, including a curriculum vitae, cover letter, and any relevant certificates. Please quote the code number 272/26 in the subject line. For further details and to submit your application, refer to the official LinkedIn advertisement:
https://www.linkedin.com/posts/stathis-megas-87530294_ai-machinelearning-phd-share-7460957042338512896-rJFz
Conclusion
This is a unique opportunity to contribute to groundbreaking research at the intersection of artificial intelligence and biomedicine, in one of Europe’s leading medical universities. If you are motivated to push the frontiers of AI in healthcare and eager to work in an inspiring international environment, you are strongly encouraged to apply. Stay tuned for similar opportunities by following the university’s updates and exploring additional positions in this rapidly evolving field.
Questions & Answers
Question: What are the main benefits of pursuing a PhD at the Medical University of Vienna?
The university offers access to world-class research facilities, a collaborative and interdisciplinary academic environment, and the chance to work on high-impact projects with leading experts. Vienna’s excellent quality of life and Austria’s supportive research ecosystem further enhance the PhD experience.
Question: What kind of projects will I work on as part of this PhD position?
You will develop advanced machine learning models for multimodal biomedical data, including single-cell omics, spatial omics, histology, and imaging, contributing to the creation of scalable and interpretable AI systems for medical research.
Question: Is previous experience in biology or medicine required for this PhD?
While a background in computer science, bioinformatics, or a related quantitative field is essential, experience at the interface of AI and biology is highly valued. Candidates with strong computational skills and an interest in biomedical applications are encouraged to apply.
Question: How can I find more information about the application process?
All application instructions and further details are provided in the official LinkedIn advertisement:
https://www.linkedin.com/posts/stathis-megas-87530294_ai-machinelearning-phd-share-7460957042338512896-rJFz
Want to calculate your PhD admission chances? Try it here:
https://phdfinder.com/phd_admission_chance_calculator/
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