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Michele Magno

3 months ago

PhD Student – Energy-Efficient Communication Systems for Next-Generation CubeSats Interdisciplinary Transformation University (IT:U) in Austria

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

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Country

Austria

University

Interdisciplinary Transformation University

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Where to contact

Official Email

Keywords

Computer Science
Electrical Engineering
Aerospace Engineering
Communication Studies
Neuromorphic Computing
Robotics
Wireless Sensor Network
Embedded System
Autonomous Robotics
Machinelearning
Signalprocessing
Drones
Spiking Neural Networks
Hardware-software Co-design

About this position

Interdisciplinary Transformation University (IT:U), Austria’s first public interdisciplinary university for digital transformation, invites applications for a PhD position in the Smart Sensing and Systems Lab (S³ Lab). The research focuses on developing energy-efficient communication systems for next-generation CubeSats, with broad applications in space, autonomous robotics, drones, and embedded wireless sensing.

The successful candidate will join a dynamic, international research environment in Linz, Austria, working under the supervision of Fellow Professor Michele Magno. The project centers on innovative embedded solutions for CubeSat communications, including efficient uplink/downlink design, low-power communication protocols, and real-time optimization for reliable data transfer in space-constrained environments. Research directions include energy-efficient communication protocols, cross-layer optimization, embedded machine learning (spiking and non-spiking networks), neuromorphic computing, TinyML, Edge AI, and advanced signal processing for adaptive data transmission and decision-making.

Students will have opportunities to collaborate on CubeSat prototypes and real-world space demonstrators, and benefit from IT:U’s strong academic and industrial network in embedded AI, space sensing, and Earth observation. Responsibilities include conducting research, publishing academic papers, attending conferences, collaborating with interdisciplinary teams, supporting teaching activities, and assisting with third-party funding applications.

Applicants should hold a master’s degree or equivalent in electrical engineering, computer science, or a related field, with strong programming skills and hardware-software co-design experience. Familiarity with deep learning frameworks (TensorFlow, PyTorch), spiking neural networks, and compartmental models is advantageous. Fluency in English (CEFR C1 or equivalent) and independent work skills are required.

The position offers a gross monthly salary starting at EUR 3,714.80 (full-time, 40h), plus the Austrian KlimaTicket Ö for unlimited public transport. The structured 4-year PhD program includes focused group work, research lab modules, project integrated courses, interdisciplinary seminars, and project assistant roles, culminating in thesis submission and defense.

Applications are open until January 31, 2026. To apply, complete the online form at https://apply.it-u.at/ and upload your CV, diplomas, transcripts, motivational letter, and up to three references. For questions or expressions of interest, contact Prof. Michele Magno at [email protected] with your CV prior to applying.

IT:U values diversity and encourages applications from all backgrounds. Join us to advance energy-efficient communication for space and intelligent systems!

Funding details

Available

What's required

Applicants must hold a master’s degree or equivalent in electrical engineering, computer science, or a relevant field. Strong programming skills and understanding of hardware-software co-design are required. Experience with deep learning frameworks such as TensorFlow and PyTorch is ideal. Working knowledge of spiking neural networks and compartmental models is a plus. Candidates must be able to work and think independently and be fluent in English at CEFR C1 level or equivalent. Applicants should be highly motivated and interested in embedded systems, edge AI, and intelligent space technologies.

How to apply

Complete the online application form and upload required documents at https://apply.it-u.at/. Submit your CV, bachelor’s and master’s diplomas and transcripts, motivational letter, and up to three references. For questions or expressions of interest, contact Prof. Michele Magno at [email protected] with your CV before applying.

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