Field of Research & Scope

We are seeking a motivated PhD student to explore innovative embedded solutions for CubeSat communications.

The research will focus on efficient uplink/downlink design, low-power communication protocols, and real-time optimization to enable reliable data transfer in space-constrained environments. We are looking for a highly enthusiastic student with a strong background in electrical engineering, communication, and hardware-software co-design to join our interdisciplinary research team at IT:U.

The successful candidate will contribute to research at the intersection of embedded systems, communication,  
and smart wireless sensing systems, with applications in autonomous robotics, drones, and space technologies.

Key research directions include:

• Energy-efficient communication protocols and cross-layer optimization for CubeSats.
• Embedded Machine Learning (spiking and non-spiking networks), with a focus on attention-based models for communication efficiency.
• Neuromorphic computing and ML-driven adaptive communication on digital and neuromorphic processors.
• TinyML and Edge AI for real-time, low-power communication and inference.
• Techniques such as quantization, pruning, knowledge distillation, and novel architectures beyond CNNs applied to communication and signal processing. 
• Real-time embedded signal processing for adaptive data transmission and decision-making. 

This project offers the opportunity to develop next-generation communication architectures for CubeSats, enabling reliable, low-power, and intelligent space communications for Earth observation and beyond.

We offer

• A dynamic, interdisciplinary research environment.
• Opportunities to collaborate on cutting-edge CubeSat prototypes and real-world space demonstrators.
• A strong academic and industrial network across embedded AI, space sensing, and Earth observation technologies.

Find out more: https://itu-s3-lab.github.io

Responsibilities & Tasks

• Conducting research.
• Writing academic publications.
• Attending national and international conferences.
• Collaborating with other research groups on an interdisciplinary basis.
• Performing auxiliary activities in academic teaching for up to 2 weekly credit hours.
• Helping to file applications for third-party funding.
• Complying with the institution’s academic standards and ethical guidelines.

Skills & Qualifications needed

• Motivated, with a strong interest in the intersection of embedded systems, edge AI, and intelligent space technologies.
• A master’s degree or equivalent in electrical engineering, computer science, or another relevant field.
• Programming skills and a solid understanding of hardware-software co-design.
• Experience with deep learning frameworks such as TensorFlow and PyTorch would be ideal.
• Working knowledge of spiking neural networks and compartmental models is a plus.
• The ability to work and think independently.
• Fluent in English (CEFR C1 or equivalent).

What you can expect

• Innovative and stimulating working conditions in an interdisciplinary, international research environment.
• Office kitchen with complimentary basic supplies.
• Austrian “KlimaTicket Ö” (unlimited travel on all public transportation within Austria).
• We offer a gross salary in line with the market from EUR 3.714,80 on a full-time basis (40h).

Program Structure

IT:U offers a 4-year, structured PhD program. 
 
In the first year, emphasis is placed on focused group work, research lab modules, and Project Integrated Courses (PICS). The first year concludes with a PhD Proposal Presentation. Over the next three years, students will develop and write their PhD theses. This is accompanied by interdisciplinary research seminars and work as a project assistant. The PhD program concludes after the 4th year with the submission and defense of the PhD thesis. 
 
Click here to view the curriculum. 

How to apply

Please fill in the online application form and upload your files at: https://apply.it-u.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

For details, questions, and expressions of interest, candidates are welcome to contact the principal investigator Michele Magno, michele.magno@it-u.at, before submitting their application. Please attach a CV to your email.

We look forward to receiving your online application.

DEADLINE:   January 31st, 2026