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) – Predicting Recovery Of Consciousness via Evidence-based Evaluation and Diagnosis (PROCEED)

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 Predicting Recovery Of Consciousness via Evidence-based Evaluation and Diagnosis (PROCEED), 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 developing novel frameworks and creating new uni- and multi-modal deep learning models for the prognosis in patients with acute brain injury — but also for general time series tasks. We are looking for an experienced AI/ML researcher to conduct high-quality interdisciplinary research in machine learning, signal processing and brain health.   
 
You will be supervised by Dr. Daniel Klotz (IT:U) and Dr. Jie Mei (IT:U), with the opportunity to collaborate with Dr. Erich Kobler (Institute for Machine Learning, Johannes Kepler University Linz), Dr. Mario Huemer (Institute of Signal Processing, Johannes Kepler University Linz) and Dr. Raimund Helbok (Department of Neurology, 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

• Developing AI/ML models to analyze data and solve real-world problems in computer vision, signal processing, and time series data analysis.
• Designing experiments to rigorously compare your methods with relevant baselines.
• Acquiring, managing, and executing research projects with collaborators.
• Publishing results in peer-reviewed international conferences and scientific journals. 

Skills & Qualifications needed

• Have completed or be in the final stages of a master’s degree in a quantitative discipline such as computer science, physics, electrical engineering, statistics and mechatronics.
• At least 1-2 years of experience in AI/ML and its applications to real-world problems.  
• Very good knowledge of the theory and practice of deep learning.  
• Experience with large-scale medical datasets (ADNI, PPMI, etc.) is a plus.
• 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.
• Proficiency in Python and its data science ecosystem (e.g., scikit-learn, PyTorch).
• Strong written and verbal communication skills.
• 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