PhD Student – Embedded Sensors and CubeSat Architectures for Earth Observation Missions Interdisciplinary Transformation University (IT:U) in Austria

Interdisciplinary Transformation University (IT:U), Austria’s first public interdisciplinary university dedicated to digital transformation, invites applications for a PhD Student position in CubeSat Design & Sensing. The research project, titled “Embedded Sensors and CubeSat Architectures for Earth Observation Missions,” is part of the IT:U Doctoral School PhD Program COMPUTATIONAL X. The successful candidate will join a dynamic, interdisciplinary environment in Linz, Austria, working closely with Fellow Professor Michele Magno.

The research focuses on innovative embedded architectures and sensor systems for CubeSats, aiming to design, prototype, and validate novel sensor nodes and their integration into CubeSat platforms. Key directions include the design and integration of embedded sensors (optical, radar, UWB, hyperspectral, event-based cameras), hardware-software co-design for energy-efficient operation, onboard embedded AI for real-time data selection and compression, development of low-power architectures and novel materials, and optimization of payload and sensor node design for Earth observation missions. Experimental validation will be conducted on prototypes and lab-based CubeSat demonstrators.

This position offers the opportunity to contribute to the next generation of CubeSat sensing systems, enabling accurate, energy-efficient, and scalable Earth observation from space. The research is at the intersection of embedded system design, sensing technologies, and space platforms, with applications in Earth monitoring, autonomous systems, and intelligent space technologies. Candidates will benefit from a strong academic and industrial network across embedded AI, space sensing, and Earth observation technologies.

Responsibilities include conducting research, writing academic publications, attending conferences, collaborating with interdisciplinary research groups, performing auxiliary teaching activities, assisting with third-party funding applications, and adhering to academic standards and ethical guidelines.

Applicants must hold a master’s degree or equivalent in electrical engineering, computer science, or a relevant field. Required skills include programming, hardware-software co-design, and fluency in English (CEFR C1 or equivalent). Experience with deep learning frameworks (TensorFlow, PyTorch) and knowledge of spiking neural networks and compartmental models are advantageous. Candidates should be motivated, independent thinkers with a strong interest in embedded systems, edge AI, and intelligent space technologies.

The position is part-time (30h/week) for up to 4 years, with a gross salary in line with the FWF of EUR 2,832.10/month. Optional supplementary contracts (teaching or research) up to 10 hours may be discussed. Additional benefits include the Austrian KlimaTicket OÖ for unlimited public transport within Upper Austria and complimentary office kitchen supplies.

The structured PhD program includes group work, research lab modules, Project Integrated Courses (PICS), interdisciplinary seminars, and project assistant work, culminating in the submission and defense of the PhD thesis after four years.

Applications must be submitted exclusively through the official application portal. Required documents include CV, diplomas, transcripts, motivational letter, and up to three contacts for recommendations. For clarifications, contact Professor Michele Magno at [email protected]. The call closes on 30 April 2026, but positions remain open until filled. Early applications are encouraged as review begins on a rolling basis. Diversity and inclusion are strongly promoted at IT:U.

For further information about the research group, visit https://itu-s3-lab.github.io.