Michele Magno

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.

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!

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.

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 .

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 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 research environment in Linz, Austria, working under the supervision of Fellow Professor Michele Magno. This PhD project focuses on the design, prototyping, and validation of innovative embedded sensor nodes for CubeSat platforms, targeting energy-efficient and real-time sensing for space-based Earth observation. Research directions include the integration of optical, radar, UWB, hyperspectral, and 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 performed on prototypes and lab-based CubeSat demonstrators. The position offers opportunities to collaborate on cutting-edge CubeSat prototypes and real-world space demonstrators, and to engage with a strong academic and industrial network across embedded AI, space sensing, and Earth observation technologies. The PhD program is structured over four years, with the first year emphasizing group work, research lab modules, and Project Integrated Courses (PICS), culminating in a PhD Proposal Presentation. Subsequent years focus on thesis development, interdisciplinary seminars, and project assistant work, concluding with thesis submission and defense. Responsibilities include conducting research, writing academic publications, attending conferences, collaborating with interdisciplinary research groups, performing auxiliary teaching activities, and assisting with third-party funding applications. The position is part-time (30h/week) with a gross salary of EUR 2,832.10 per month, in line with FWF standards. Optional supplementary contracts for 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 access to an office kitchen with complimentary supplies. Applicants must have a master’s degree or equivalent in electrical engineering, computer science, or a relevant field, strong programming skills, and a solid understanding of hardware-software co-design. Experience with deep learning frameworks (TensorFlow, PyTorch) is ideal, and knowledge of spiking neural networks and compartmental models is a plus. Fluency in English (CEFR C1 or equivalent) and independent work skills are required. Only candidates whose background closely matches the requirements should apply. To apply, submit your application via the official portal, including CV, diplomas, transcripts, motivational letter, and up to three contacts for recommendations. For clarifications, contact Professor Magno at [email protected] before applying. Applications sent by email will not be considered. The position remains open until filled, with a final deadline of 30 April 2026. Early applications are encouraged as review is rolling. IT:U values diversity and encourages applications from all backgrounds. The research environment is innovative, interdisciplinary, and international, offering stimulating conditions for academic growth and contribution to next-generation CubeSat sensing systems for Earth observation.