Field of Research & Scope

We are seeking a motivated PhD student to explore innovative embedded architectures and sensor systems for CubeSats. The research will focus on designing, prototyping, and validating novel sensor nodes, their integration into CubeSat platforms, and enabling energy-efficient and real-time sensing for space-based Earth observation. Candidates with a strong background in electrical engineering, embedded systems, sensors, or hardware-software co-design are encouraged to apply.

The successful candidate will contribute to research at the intersection of embedded system design, sensing technologies, and space platforms, with applications in Earth monitoring, autonomous systems, and intelligent space technologies.

Key research directions include:

• Design and integration of embedded sensors (e.g., optical, radar, UWB, hyperspectral, or event-based cameras) for CubeSats.
• Hardware-software co-design of CubeSat subsystems for energy-efficient operation in constrained environments.
• Onboard embedded AI and real-time processing for intelligent data selection and compression.
• Development of low-power architectures and novel materials for compact and reliable sensing platforms.
• Optimization of payload and sensor node design for Earth observation missions.
• Experimental validation on prototypes and lab-based CubeSat demonstrators.

This project offers the opportunity to contribute to the next generation of CubeSat sensing systems, enabling accurate, energy-efficient, and scalable Earth observation from space.

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