IT:U is Austria‘s first public interdisciplinary university dedicated to digital transformation for the benefit of our society, economy, and environment.

PTM (Personalized Technical Medicine) – Integration of Novel biomarkers for Detection, Evaluation of Early Signatures, and Developmental insights of Parkinson's Disease (INDEED-PD)

Field of Research & Scope

The aim of the Upper Austrian Research Initiative PTM is to set new standards in medical technology research through close inter-university collaboration among IT:U, JKU and FH OÖ.  
 
In particular, the initiative seeks to advance the development of personalized prevention, diagnostic, and therapeutic solutions, promote innovative research projects at the intersection of medicine and technology, and sustainably strengthen Upper Austria as a hub for science, research, and innovation. 
 
For the interdisciplinary research project Integration of Novel biomarkers for Detection, Evaluation of Early Signatures, and Developmental insights of Parkinson's Disease (INDEED-PD), conducted in cooperation between IT:U, JKU, Medical Faculty of JKU, and KUK, we are seeking a highly motivated individual to join the team as a PhD Student).  
 
The project focuses on integrating multi-modal data (EEG, ECG, (f)MRI, etc.) with cutting edge AI analytical approaches to enable the early detection and subtyping of Parkinson’s Disease. The selected PhD student will work as part of a multidisciplinary team of experienced researchers, closely collaborating with another PhD candidate who will focus on the development of uni- and multi-modal deep learning models.  
 
You will be supervised by Dr. Spiros Denaxas (IT:U, UCL) and Dr. Jie Mei (IT:U), with the opportunity to collaborate with Dr. Erich Kobler (Institute for Machine Learning, Johannes Kepler University Linz), Dr. Daniel Klotz (IT:U) and Dr. Kai Loewenbrück (Klinik für Neurologie, Kepler University Hospital). 
 
The four-year fixed-term position as a PhD Student (holding a Diploma or Maste’s degree) with a workload of 40 hours per week offers structured supervision, hands-on laboratory and research experience, and comprehensive scientific training. The aim is to develop both subject-specific expertise and transferable skills, providing an excellent foundation for a successful academic and research career. 

Program Structure

IT:U offers a 3-year, structured PhD program. It is planned that students can finish their PhD in 4 years as the project has a duration of 4 years.   
  
The first semester concludes with a PhD Progress Presentation. Over the next years, students will develop and write their PhD theses. This is accompanied by interdisciplinary research seminars.  
The PhD program concludes with the submission and defense of the PhD thesis.  
  
 

We offer

• Collaborations: cross-disciplinary collaborations with research labs at JKU, KUK, and IT:U.
• Dynamic research environment
• Professional and personal development
• State-of-the-art research infrastructure
• Attractive campus environment with good public transportation connections  

Responsibilities & Tasks

• Perform research both independently and in a team.
• Completing a doctorate/PhD degree in health data science and writing academic publications.
• Present your scientific results in publications at international scientific conferences and in scientific journals collaborating with other research groups on an interdisciplinary basis.
• Performing auxiliary activities in academic teaching for up to 2 weekly credit hours.
• Participate in administrative and organizational tasks of the hosting institutes complying with the institution’s academic standards and ethical guidelines. 

Skills & Qualifications needed

• Motivated, with a strong interest in the intersection of health data science, neuroscience, machine learning and clinical sciences.
• A degree or experience equivalent to a Master's degree in fields such as machine learning, artificial intelligence, health data science, etc.  
• Excellent knowledge of scientific programming using Python
• Excellent practical knowledge of key machine learning (supervised and unsupervised) concepts in the context of health data.
• Experience with electronic health records and medical ontologies.
• An interest in computational modeling of brain circuitry in health and disease is a plus.
• The ability to work and think both independently and in team settings.  
• Fluent in English (written and spoken). 

What you can expect

• Innovative and stimulating working conditions in an interdisciplinary, international research environment
• Office kitchen with complimentary basic supplies
• Climate Ticket Upper Austria (optimal public transportation connections)
• We offer a gross salary in line with the FWF salary rate of EUR 3.776,13 (40h).

How to apply

Please fill in the online application form and upload your files at:  
 
 

• Curriculum Vitae
• Bachelor’s and Master’s diploma (or equivalent)  
• Bachelor's and Master’s Transcript of Records
• Motivational letter
• Up to 3 contacts of professors/collaborators for recommendations 

We look forward to receiving your online application. 

Application deadline: August 5, 2026