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Schahram Dustdar

7 months ago

Prae-doc Project Assistant: AI-Driven Modelling for Internet-of-Energy (IoE) TU Wien in Austria

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Austria

University

TU Wien

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Keywords

Computer Science
Machine Learning
Environmental Science
Electrical Engineering
Information Technology
Mathematics
Artificial Intelligence
Cloud Computing
Edge Computing
Internet Of Things
Distributed System
Digital Twins

About this position

The Research Division Distributed Systems at the Institute of Information Systems Engineering, TU Wien, invites applications for a full-time prae-doc project assistant position, funded for 36 months under the EU Marie Skłodowska-Curie Doctoral Network "SAILING." The project focuses on the Internet-of-Energy (IoE), a rapidly evolving ecosystem driven by clean energy and decarbonization initiatives. The integration of renewable energy sources, smart devices, and the demand for resilient energy infrastructure has introduced unprecedented complexity to modern power systems. Traditional modelling tools are insufficient for capturing the real-time, nonlinear, and multiscale dynamics of these systems.

This PhD project aims to address these challenges by developing advanced AI methodologies, particularly adversarial machine learning, to create reliable, scalable, and interpretable digital twins of complex energy systems. The research will enable real-time simulation and analysis, supporting intelligent decision-making and efficient energy management. The position is part of the SAILING Doctoral Network, which trains 12 doctoral candidates across academic and industrial partners, offering international secondments and collaborative training opportunities.

Applicants should have a strong MSc or equivalent degree in computer science, informatics, business informatics, or a related field. Required expertise includes distributed systems, edge/cloud/elastic computing, autonomic complex systems, IoT, machine learning, probabilistic machine learning, and mathematics. Experience with generative and adversarial models, active inference, and reliable AI strategies is advantageous. Candidates must demonstrate motivation for independent research, interdisciplinary collaboration, and excellent English communication skills. Social and gender competence, teamwork, and experience in national/international research cooperation are expected.

Eligibility is governed by the EU Horizon Europe Marie Skłodowska-Curie Action Doctoral Networks scheme: candidates must not already possess a doctoral degree and must comply with the mobility rule (not have resided or carried out main activity in Austria for more than 12 months in the 36 months before recruitment). European and international applicants are welcome, subject to visa regulations.

The position offers a competitive salary (€3,776.10/month gross, paid 14 times per year), mobility and family allowances, access to state-of-the-art hardware and software, continuing education, and opportunities to present research at international conferences. The work environment is creative, young, and international, with attractive social benefits. TU Wien encourages applications from women and follows an open, transparent, and equitable recruitment process.

To apply, submit a single PDF containing your motivation letter, CV, certificates, list of publications, and thesis by email to Christine Kamper ([email protected]). For further information, contact Prof. Schahram Dustdar ([email protected]). The application deadline is March 16, 2026.

Funding details

Available

What's required

Applicants must hold a good MSc or comparable degree in computer science, informatics, business informatics, or a related discipline. Excellent knowledge and scientific achievements in distributed systems, edge/cloud/elastic computing, autonomic complex systems, and IoT are required. Strong foundation in machine learning, probabilistic machine learning, and mathematics is essential. Knowledge of generative and adversarial models, active inference, and reliable AI strategies is a plus. Candidates must demonstrate motivation for independent research, ability to develop and evaluate methods and models, willingness to collaborate in interdisciplinary teams, and experience in national/international research cooperation. Very good English communication and writing skills, social and gender competence, and teamwork are expected. Applicants must not already possess a doctoral degree and must comply with the MSCA DN mobility rule (not have resided or carried out main activity in Austria for more than 12 months in the 36 months before recruitment).

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Professors

Professor at TU Wien

University Name
Country flag

Austria

Research Interests

Internet Of Things

Cloud Computing

Edge Computing

Distributed System

Data Sharing