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Michele Magno

Fellow Professor at Interdisciplinary Transformation University (IT:U)

Interdisciplinary Transformation University

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Austria

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Research Interests

Aerospace Engineering

30%

Electrical Engineering

30%

Computer Science

30%

Embedded System

30%

Communication Studies

20%

Robotics

20%

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Positions3

Publisher
source

Michele Magno

University Name
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Interdisciplinary Transformation University (IT:U)

PhD Student – Energy-Efficient Communication Systems for Next-Generation CubeSats

The Interdisciplinary Transformation University (IT:U) in Austria invites applications for a PhD position focused on “Energy-Efficient Communication Systems for Next-Generation CubeSats.” This opportunity is part of the IT:U Doctoral School’s COMPUTATIONAL X PhD program and is based in the Smart Sensing and Systems Lab (S³ Lab) in Linz. The position is full-time, up to 4 years, and starts in March 2026 under the supervision of Fellow Professor Michele Magno. The research centers on developing innovative embedded solutions for CubeSat communications, emphasizing efficient uplink/downlink design, low-power communication protocols, and real-time optimization for reliable data transfer in space-constrained environments. The successful candidate will work at the intersection of embedded systems, communication, and smart wireless sensing, with applications in autonomous robotics, drones, and space technologies. Key research directions include energy-efficient communication protocols, cross-layer optimization for CubeSats, embedded machine learning (including spiking and non-spiking networks), neuromorphic computing, TinyML, Edge AI, and advanced signal processing techniques. The project aims to enable reliable, low-power, and intelligent space communications for Earth observation and related applications. IT:U offers a dynamic, interdisciplinary research environment with opportunities to collaborate on cutting-edge CubeSat prototypes and real-world space demonstrators. The university provides a strong academic and industrial network across embedded AI, space sensing, and Earth observation technologies. The position includes a competitive gross salary starting from EUR 3,714.80/month (full-time, 40h) and the Austrian KlimaTicket Ö for unlimited public transportation within Austria. Applicants should have a master’s degree or equivalent in electrical engineering, computer science, or a related field, with strong programming skills and experience in hardware-software co-design. Familiarity with deep learning frameworks (TensorFlow, PyTorch), spiking neural networks, and compartmental models is advantageous. Fluency in English (CEFR C1 or equivalent) is required. The structured 4-year PhD program includes focused group work, research lab modules, and interdisciplinary seminars, culminating in a PhD thesis and defense. The application deadline is January 31, 2026. For more information about the lab, visit https://itu-s3-lab.github.io . To apply, complete the online form at https://apply.it-u.at/ and upload your CV, diplomas, transcripts, motivational letter, and up to three recommendation contacts. For questions or expressions of interest, contact Prof. Michele Magno at [email protected] before submitting your application.

1 month ago

Publisher
source

Michele Magno

University Name
.

Interdisciplinary Transformation University (IT:U)

PhD Student – Energy-Efficient Communication Systems for Next-Generation CubeSats

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!

1 month ago

Publisher
source

Michele Magno

University Name
.

Interdisciplinary Transformation University (IT:U)

PhD Student - CubeSat Design & Sensing: Embedded Sensors and CubeSat Architectures for Earth Observation Missions

The Interdisciplinary Transformation University (IT:U) in Austria is offering a fully funded PhD position in CubeSat Design & Sensing, focusing on embedded sensors and CubeSat architectures for Earth observation missions. This opportunity is part of the IT:U Doctoral School’s COMPUTATIONAL X PhD program and is based in Linz, Austria, with a start date in March 2026. The position is supervised by Professor Michele Magno, principal investigator and head of the Smart Sensing and Systems Lab (S³ Lab). The research project centers on the design, prototyping, and validation of innovative embedded sensor nodes and their integration into CubeSat platforms. The successful candidate will work on energy-efficient and real-time sensing solutions for space-based Earth observation, contributing to the next generation of CubeSat technologies. Key research areas include the design and integration of advanced sensors (optical, radar, hyperspectral, event-based cameras), hardware-software co-design for CubeSat subsystems, onboard embedded AI for intelligent data selection and compression, development of low-power architectures and novel materials, and optimization of payload and sensor node design. Experimental validation will be conducted using prototypes and lab-based CubeSat demonstrators. The position offers a dynamic, interdisciplinary research environment with opportunities to collaborate on cutting-edge CubeSat prototypes and real-world space demonstrators. IT:U provides access to a strong academic and industrial network in embedded AI, space sensing, and Earth observation technologies. The PhD program is structured over four years, beginning with focused group work, research lab modules, and project-integrated courses, followed by thesis development, interdisciplinary seminars, and project assistant work. The program concludes with the submission and defense of the PhD thesis. Applicants should have a master’s degree or equivalent in electrical engineering, computer science, or a related field, with strong programming skills and experience in hardware-software co-design. Familiarity with deep learning frameworks (TensorFlow, PyTorch) and knowledge of spiking neural networks and compartmental models are advantageous. Fluency in English (CEFR C1 or equivalent) and the ability to work independently are required. The position offers a competitive gross salary starting from EUR 3,714.80 per month (full-time, 40h), as well as the Austrian KlimaTicket Ö for unlimited public transport within Austria. Additional benefits include a collaborative and inclusive work environment, office kitchen with complimentary supplies, and support for conference attendance and academic development. To apply, candidates must submit an online application at https://apply.it-u.at/ , including a CV, bachelor’s and master’s diplomas and transcripts, motivational letter, and up to three contacts for recommendations. For questions or expressions of interest, applicants may contact Professor Michele Magno at [email protected] with their CV prior to applying. The application deadline is January 31st, 2026. IT:U values diversity and encourages applications from all backgrounds.

1 month ago