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Master Thesis "Meta Learning in Nonlineary Dynamic System Modelling"
Austrian Institute of Technology —Wien, W
The focus of this master’s thesis is the investigation of meta learning techniques for fast model adaptation in low-data scenarios.

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Master Thesis “Differentiable Ray Tracing for Radio Propagation Modeling”

Austrian Institute of Technology -
Wien, W

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Details zur Stelle

Qualifikationen

Master

Vollständige Stellenbeschreibung

As Austria's largest research and technology organisation for applied research, we are dedicated to making substantial contributions to solving the major challenges of our time, climate change and digitalisation. With our open culture of innovation and our motivated, international teams, we are working to position AIT as Austria's leading research institution at the highest international level and to make a positive contribution to the economy and society.

Our Center for Digital Safety & Security located in Vienna invites applications for a master’s thesis position in the Reliable Wireless Communication and Sensing research group. As part of our research team, you will support us within our research projects, focusing on reliable wireless 5G/6G communication and sensing.

Master Thesis “Differentiable Ray Tracing for Radio Propagation Modeling”

CENTER FOR DIGITAL SAFETY & SECURITY

Differentiable ray-tracing frameworks such as Sionna RT have become powerful tools for wireless channel modeling. This master's thesis advances differentiable ray tracing for realistic large-scale radio propagation, either by integrating atmospheric refraction models or by learning electromagnetic environment properties directly from channel measurements.
Under the guidance of our team, you will implement and evaluate atmospheric refraction models in the differentiable ray-tracing framework Sionna RT.
You will implement and evaluate differentiable algorithms for estimating electromagnetic material properties from real-world channel measurements.
You will learn how to develop and validate simulation workflows for large-scale radio propagation, combining physics-based propagation models with discrete ray tracing, low-complexity ray-shooting, and gradient-based optimisation techniques.

You will gain hands-on experience with modern wireless communication simulation frameworks, electromagnetic wave propagation, physics-based and inverse modeling, and AI-enabled optimisation methods.
You will work closely with researchers in wireless communications and contribute to the development of next-generation ray-tracing methods for realistic large-scale propagation prediction.

Your qualifications:

You are pursuing a master's degree in Electrical Engineering, Computer Science, Telecommunications, Physics, or a related field.
First experience(e.g. gained through university / student research projects, laboratory work, internships or similar activities) in at least one of the following areas: (i) atmospheric refraction modeling for ray tracing or (ii) learning of environment properties using differentiable ray tracing. In the cover letter, the candidate shall describe how their CV and personal interests for future development match at least one of the above profiles (explicitly referring to (i) or (ii)) and substantiate their claimed expertise. Please note that applications that do not address this point may not be considered further.
You have solid programming skills in Python; experience with object-oriented software development is an advantage.
You have a basic understanding of electromagnetics, wave propagation, wireless communications, or computer graphics.
Knowledge of ray tracing, geometric optics, optimisation methods, or machine learning is beneficial but not required.
Experience with scientific computing frameworks (e.g., NumPy, TensorFlow, PyTorch, or Sionna) is a plus.
You enjoy developing algorithms and solving challenging scientific and engineering problems.
You are able to work independently while collaborating effectively in an interdisciplinary research team.
Good written and spoken English skills are required.

What to expect:

Duration of the master’s thesis project: 6 months
Start date: ideally 01.10.2026 – however, there is some flexibility regarding the start date
EUR 1.379,60 gross per month for 20 hours/week.
Dedicated guidance and supervision from our experienced researchers, who will support you throughout your final thesis - from the initial concept to the final results.
Highlights of our employee benefits include a canteen and meal allowance, organic coffee, tea and fruit baskets, preventive healthcare benefits and company doctor, additional days off for various life events, leisure subsidies, voucher programme, sports, cultural and socialising events, as well as flexitime models (incl. home office possibilities).

At AIT, we create an inclusive and family-friendly working environment that promotes equal opportunities and actively strengthens diversity across our workforce and in leadership positions. Among other initiatives, we are committed to increasing the proportion of women in our company and therefore particularly welcome applications from female applicants.

Please submit your complete application documents online, consisting of your CV, a cover letter, relevant certificates (transcript of records), as well as a proof of identity.

Apply now!

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