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Interdisciplinary Transformation University

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PhD Student (f/m/d) in Personalized Technical Medicine: Predicting Recovery of Consciousness via Evidence-based Evaluation and Diagnosis (PROCEED) Interdisciplinary Transformation University (IT:U) in Austria

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

Aug 5, 2026

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Country

Austria

University

Interdisciplinary Transformation University

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Keywords

Computer Science
Neurology
Biomedical Engineering
Signal Processing
Electrical Engineering
Deep Learning
Artificial Intelligence
Medical Technology
Time Series Analysis
Computer Vision
Python Programming
Neuropsychology
Medical Science
Computational Modelling
Statistics
Machine learning

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About this position

Interdisciplinary Transformation University (IT:U) in Linz, Austria is offering one PhD position in the IT:U Doctoral School / PhD Program in Interdisciplinary Computing for the project PROCEED (Predicting Recovery Of Consciousness via Evidence-based Evaluation and Diagnosis).

This is an interdisciplinary, on-site PhD opportunity in personalized technical medicine, carried out in cooperation with Johannes Kepler University Linz, the JKU Medical Faculty, and Kepler University Hospital. The project sits at the intersection of medical technology, machine learning, signal processing, neuroscience, and brain health, with a focus on building novel uni- and multi-modal deep learning frameworks for prognosis in patients with acute brain injury and related time-series tasks.

You will work in a structured research and training environment with supervision by Dr. Daniel Klotz and Dr. Jie Mei, and collaboration opportunities with researchers at JKU and the hospital partner network. The position offers cross-disciplinary teamwork, state-of-the-art research infrastructure, and a dynamic international environment.

Typical tasks include developing AI/ML models, designing rigorous experiments, comparing methods against baselines, managing collaborative research activities, and publishing in peer-reviewed conferences and journals. The role is suited to candidates with a strong quantitative background and substantial experience in machine learning and deep learning.

Eligibility highlights include a completed or nearly completed master’s degree in a quantitative field such as computer science, physics, electrical engineering, statistics, or mechatronics; 1–2 years of AI/ML experience; strong Python skills; and fluent English. Familiarity with medical datasets such as ADNI or PPMI is an advantage, as is interest in computational modeling of brain circuitry in health and disease.

The appointment is a four-year fixed-term PhD position with full-time workload (40 hours/week). The salary is aligned with the FWF rate of EUR 3,776.13 gross per month. The application deadline is 5 August 2026, and applications are submitted online via the IT:U careers portal.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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