PhD programmes - Science and Technology

Details about funded positions - 40th Cycle - Curriculum 6

(6A) Radiation hard photonic integrated circuits for space applications (PNRR_NQSTIS6, CUP I53C22001460006)

Funding institution: National Institute of Nuclear Physics - INFN
Doctoral site: Sant’Anna School of Advanced Studies - Pisa
Contact: Prof. Claudio Jose Oton Nieto [claudio.oton [at] santannapisa.it]
Funds: Project Funds (PNRR_NQSTIS6, CUP I53C22001460006)
Mobility abroad: compulsory, minimum 6 months
Periods in companies/research centres/public administrations: optional

Silicon photonics (SiPh) can provide the enabling technology for high-radiation environment telecom and sensing applications such as in space and particle accelerators like the LHC at CERN. SiPh is becoming a disruptive technology for reducing the size, weight, cost and power consumption of optical fibre transmission networks and optical fibre sensor systems.  SiPh promises low-cost and high-volume production, complementary metal-oxide-semiconductor (CMOS) compatibility and the potential for monolithic integration with electronics. The most widely developed platform utilises Si-on-insulator (SOI) nanowire waveguides and has been extended to include integrated active components such as modulators and photodetectors. 
The proposed research will focus on design and characterization of radiation-hard silicon photonic building blocks for communication and sensing applications. The performance of systems on chips, such as sensor reading units and transceivers, will be investigated under high radiation conditions.

(6B) Model-based system-software engineering and formal methods for space systems

Funding institution: Fondazione Bruno Kessler - FBK
Doctoral site: Fondazione Bruno Kessler - FBK
Contact: Dr. Marco Bozzano [bozzano [at] fbk.eu]
Funds: Own Funds
Mobility abroad: compulsory, minimum 6 months
Periods in companies/research centres/public administrations: optional

Space systems have reached an unprecedented degree of complexity. The design process has to guarantee not only the functional correctness of the implemented system but also its dependability and resilience concerning run-time faults. Hence, the design process must characterise the likelihood of faults, mitigate possible failures, and assess the effectiveness of the adopted mitigation measures.
Formal methods have been increasingly used over the last decades to deal with the shortcomings of designing complex systems, in different domains. Formal methods are based on the adoption of a formal, mathematical model of the system, shared between all actors involved in the system design, and on a tool-supported methodology to aid all the steps of the design, from the definition of the architecture down to the final implementation in HW and SW. 
The objective of this study is to advance the state-of-the-art space system design using formal methods. In particular, it will investigate new techniques for model-based systems and software engineering, to support the design, mission preparation and operations of space systems. The potential research directions include fault detection, isolation, and recovery (FDIR) for satellites; system-level diagnosis and diagnosability based on telemetry; and digital twins for satellites. Topics to be investigated include techniques for contract-based design and contract-based safety assessment, advanced verification techniques based on compositional reasoning, the analysis of the timing aspects of fault propagation, the characterization of transient and sporadic faults, the analysis of the effectiveness of fault mitigation measures in presence of complex fault patterns, and the modelling and analysis of systems with continuous and hybrid dynamics. 
The developed techniques will be implemented and evaluated using tools for system-software engineering such as the COMPASS tool and the COMPASTA tool, based on the TASTE toolchain. The topics of the PhD are aligned with the AIFDIR (Design, Verification and Validation of AI-based FDIR) and ExploDTwin (Digital Twin for Space Exploration Assets) projects, funded by the Italian and European Space Agencies.

(6C) Digital technologies for satellite communications and their integration in non-terrestrial networks

Funding institution: CNIT - National Inter-University Consortium for Telecommunications
Doctoral site: CNIT - National Inter-University Consortium for Telecommunications - Research Unit Parma
Contact: Dr. Armando Vannucci [armando.vannucci [at] unipr.it]
Funds: Own Funds
Mobility abroad: compulsory, minimum 6 months
Periods in companies/research centres/public administrations: optional

Future 6G wireless networks will provide ubiquitous broadband coverage even in underserved areas. To this aim, 6G research is currently focusing on the development of non-terrestrial networks (NTN). NTNs integrate non-terrestrial devices, including UAVs, high-altitude platforms, and satellites. Among these, low-Earth-orbit (LEO) satellite mega-constellations have attracted a huge interest.
In this framework, several challenges will be addressed in this PhD activity. First of all, the selection of the modulation format. Indeed, due to the presence of Doppler shifts, orthogonal frequency division multiplexing (OFDM) does not appear the ideal choice, and suitable alternatives have to be considered. Macro diversity, i.e., the joint use of several T/NT nodes to serve the same User Terminal (UT), can be exploited as an effective way to ensure a more uniform throughput even when the UT is located in underserved areas. Practical implementation of macro-diversity poses several technical challenges, due to the need to combine at the UT two or more paths possibly arriving at different epochs, and with different Doppler frequencies and phases. 

(6D) Metallic additive manufacturing advancements for aerospace innovation in microsatellites (CUP E66E24000000001)

Funding institution: Trentino Sviluppo S.p.A.
Doctoral site: Trentino Sviluppo S.p.A. - ProM Facility & University of Trento
Contact: Prof. Nicola Pugno [nicola.pugno [at] unitn.it]; Prof. Roberto Battiston [roberto.battiston [at] unitn.it]; Dr. Paolo Gregori [paolo.gregori [at] trentinosviluppo.it]
Funds: NRRP, M4C2 Inv. 3.3, Innovative PhDs​​​​​​​
Mobility abroad: compulsory, minimum 6 months​​​​​​​
Periods in companies/research centres/public administrations: compulsory, minimum 6 months

The proposed doctoral scholarship, jointly promoted by the University of Trento and co-financed by ProM Facility of Trentino Sviluppo, focuses on advancing cutting-edge competencies in the field of metallic additive manufacturing applied to aerospace technologies. The successful candidate will have the unique opportunity to synergize generative design approaches and digital twin simulations available at the University of Trento with state-of-the-art machinery at ProM Facility. Key aspects of this PhD program include Generative Design Approach: The candidate will explore innovative design methodologies, leveraging generative algorithms to create optimised structures for additive manufacturing. Digital Twin Simulations: by harnessing digital twin technology, the candidate will simulate and validate the performance of additive-manufactured components ensuring their reliability and functionality.Advanced Manufacturing Technologies: ProM Facility offers cutting-edge resources, including 3D metal printers (for materials such as titanium, aluminium, and Inconel), X-ray tomography, reverse engineering capabilities, and integration of sensors and artificial intelligence. The research will specifically explore aerospace applications, with a specific focus on microsatellites—a frontier in future telecommunications. In summary, this industrial doctoral scholarship provides a unique blend of theoretical knowledge, practical skills, and hands-on experience, positioning the candidate at the forefront of metallic additive manufacturing advancements for aerospace innovation.

(6E) Development of innovative mechatronic systems for scientific and technological payloads for space and exploration missions (CUP E66E24000000001)

Funding institution: OHB Italia​​​​​​​
Doctoral site: OHB Italia & University of Trento​​​​​​​
Contact: Prof. Daniele Bortoluzzi [daniele.bortoluzzi [at] unitn.it]
Funds: NRRP, M4C2 Inv. 3.3, Innovative PhDs​​​​​​​
Mobility abroad: compulsory, minimum 6 months​​​​​​​
Periods in companies/research centres/public administrations: compulsory, minimum 6 months

The project objectives aim at the realisation, qualification and validation of innovative mechatronic systems for space payloads and the simultaneous training of a high-profile professional figure capable of understanding, designing and implementing a space system. The activity plan envisages training through frontal/laboratory teaching at the PhD School, participation in project activities (in collaboration with OHB, ESA, ASI and other partners), in-depth scientific studies and the production of new skills. The expected results lie in project collaboration activities on space missions (contribution to project milestones), scientific and technological creation and dissemination, synergies with project partners and spin-offs on potential new space missions.

(6F) Navigation techniques based on satellite signals and image processing images (CUP E66E24000000001)

Funding institution: QAscom​​​​​​​
Doctoral site: QAscom & University of Trento​​​​​​​
Contact: Prof. Claudio Sacchi [claudio.sacchi [at] unitn.it]
Funds: NRRP, M4C2 Inv. 3.3, Innovative PhDs​​​​​​​
Mobility abroad: compulsory, minimum 6 months​​​​​​​
Periods in companies/research centres/public administrations: compulsory, minimum 6 months

The objectives of the activity are as follows:

  • Study of innovative navigation techniques based on satellite signals and image processing;
  • Development of software simulators to quantify the performance and benefits of the proposed techniques.

Over the three years, the PhD student will have to:

  • Acquire knowledge related to satellite navigation techniques through review of the state of the art and interaction with experts in the field in the academic and corporate worlds;
  • Acquire knowledge related to visual-based navigation techniques through review of the state of the art and interaction with industry experts in the world academic and corporate worlds;
  • Propose innovative navigation techniques as one of the concepts to be considered, as a minimum, the doctoral candidate will have to analyse the integration between techniques based on Radio Frequency (RF) signal transmissions by constellations dedicated to navigation (e.g., GNSS) and techniques based on image processing of images;
  • Develop software simulators to quantify the performance and benefits of the proposed techniques;
  • Disseminate the results found, through scientific publications and presentations of their work;
  • Carry out a research period at Qascom and at a foreign institution.

(6G) FPGA based Large scale interferometry, ultra precise syncronization (CUP E66E24000000001)

Funding institution: SANITAS E.G.​​​​​​​
Doctoral site: SANITAS E.G. & Istituto Universitario di Studi Superiori - IUSS Pavia​​​​​​​
Contact: Prof. Paolo Esposito [paolo.esposito [at] iusspavia.it]; Sandro Pastore [sandro.pastore [at] sanitaseg.it]; Gabriele Sorrenti [gabriele.sorrenti [at] sanitaseg.it]
Funds: NRRP, M4C2 Inv. 3.3, Innovative PhDs​​​​​​​
Mobility abroad: compulsory, minimum 6 months​​​​​​​
Periods in companies/research centres/public administrations: compulsory, minimum 6 months

Last available FPGA technologies allow very fine time management and rich logic resources to implement new observation instruments. Precise and stable time synchronization is a common requirement to correlate acquisition data from distributed systems. Several time sources are available and shall be managed to obtain a stable and deterministic distributed acquisition system. The candidate shall be interested in the technology challenge related to the implementation of low level FPGA code and analog integration to obtain the best possible time reference for signal sampling. The candidate shall be able to understand the available standard and resources and set up a laboratory to verify and validate the proposed solution. The candidate will be supported by the twenty years of experience in FPGA development and instrument development from Sanitas and its collaborators (national and international research laboratory). This research activity will offer the opportunity to acquire a deep Know-How requested by several instruments, for both scientific and commercial purposes. FPGA knowledge will be increased to find and validate high performance circuits.

(6H) Development of millimetre/sub-millimetre-wave components for Space payloads through Advanced Manufacturing

Funding institution: National Research Council of Italy - CNR​​​​​​​
Doctoral site: CNR-IEIIT (Turin) or CNR-STIIMA (Milan)​​​​​​​
Contact: Dr. Oscar Antonio Peverini [oscarantonio.peverini [at] cnr.it]; Dr. Irene Fassi [irene.fassi [at] stiima.cnr.it]
Funds: Own Funds​​​​​​​
Mobility abroad: compulsory, minimum 6 months​​​​​​​
Periods in companies/research centres/public administrations: optional

Within this PhD, the candidate will investigate the manufacturability of radiofrequency breadboards for Space applications exploiting advanced manufacturing technologies, both subtractive, such as micro-EDM, and additive, such as metal extrusion-based additive manufacturing and precision 3D printing of functionally graded materials. 
Indeed, next-generation payloads for SATCOM (in GEO and LEO orbits), Earth Observation, and Space Science will require high-volume production of high-performance RF instrumentation operating from the Ka/Q/V bands (30-50 GHz) up to sub-millimetre frequencies (200-600 GHz). These applications require manufacturing technologies able to fabricate high-precision components with complex geometry and accurate micro-features, with high throughput, zero waste and sustainable footprint. 
In this context, precision manufacturing technologies play an enabling role in the development of innovative payloads in terms of performance and compatibility with platforms. This multi-disciplinary study will be carried out at the two institutes STIIMA (https://www.stiima.cnr.it) and IEIIT (https://www.ieiit.cnr.it) of the CNR in synergy with the research activities that the CNR carries out within European Space Agency programmes.

(6I) Deep Learning techniques for inverse problem in imaging (CUP E66E24000000001)

Funding institution: Fasternet S.r.l​​​​​​​
Doctoral site: Fasternet S.r.l. & University of Brescia​​​​​​​
Contact: Prof. Davide Pagano [davide.pagano [at] unibs.it]
Funds: NRRP, M4C2 Inv. 3.3, Innovative PhDs​​​​​​​
Mobility abroad: compulsory, minimum 6 months​​​​​​​
Periods in companies/research centres/public administrations: compulsory, minimum 6 months

Inverse problems deal with the reconstruction of an unknown signal, image, or multi-dimensional volume from a set of observations, which are generally the result of a non-invertible forward process. A wide range of scenarios fall within this definition, such as deconvolution, image deblurring, inpainting, and so on. As inverse problems are usually ill-posed, in general, it is not possible to find a unique solution that describes the observation, unless some prior knowledge about the data is available. Traditional approaches, based on the minimisation of a cost function and a regularizer taking into account possible prior knowledge of data, are found to underperform with respect to recent deep learning techniques. The goal of the project is to explore the potentiality of some modern deep learning techniques in selected imaging cases, such as muography and medical imaging, which are relevant to science and industry.

(6L) Optical Fiber Sensor Systems for Space Applications (E66E24000000001)

Funding institution: Infibra Technologies S.r.l.​​​​​​​
Doctoral site: Infibra Technologies S.r.l. & Sant’Anna School of Advanced Studies Pisa​​​​​​​
Contact: Prof. Claudio Jose Oton Nieto [claudio.oton [at] santannapisa.it]
Funds: NRRP, M4C2 Inv. 3.3, Innovative PhDs
Mobility abroad: compulsory, minimum 6 months​​​​​​​
Periods in companies/research centres/public administrations: compulsory, minimum 6 months

Optical fibre sensor technology provides attractive solutions for monitoring modern spacecraft and launch vehicles. Smart space structures embedded with optical fibre sensors allow for increased performance and reliability in harsh environments with additional advantages due to reduction in mass, size and power consumption. Optical fibre sensors embedded in smart carbon fibre structures allow for accurate realtime measurement of temperature as well as monitoring structural integrity. Optical fibre sensors can be used in on-ground qualification, pre-flight testing, as well as in-flight and in-orbit operations, requiring the sensor reading units to be realised in compact form, resistant to harsh environments and with reduced mass, size and power consumption. Silicon photonics (SiPh) provides a disruptive technology for satisfying these requirements.
Addressing the design and development of specific smart space structures embedded with optical fibre sensors and their reading units will be the main subject of this PhD.
Addressing the design and development of specific smart space structures embedded with optical fibre sensors and their reading units will be the main subject of this PhD.

(6M)  ASI SPACE IT UP SPOKE 5 – Artificial Intelligence and machine learning for the analysis of multisensory and multitemporal Earth observation data (CUP E63C24000530003)

Funding institution: University of Trento
Doctoral site:  University of Trento
Contact: Prof. Lorenzo Bruzzone [lorenzo.bruzzone [at] unitn.it]
Funds: Project Funds
Mobility abroad: compulsory, minimum 6 months
Periods in companies/research centres/public administrations: Optional

The automatic analysis of image time series acquired by single and/or multimodal (multisensor, multiplatform, multiscale) Earth observation satellites is crucial for many different applications. One of the most important applications is related to complex problems related to natural disaster prediction/prevention and monitoring. In this context, even if artificial intelligence and machine learning have been used for the automatic analysis of remote sensing data, there are still many methodological challenges and application issues that should be addressed in the analysis of long-time series of satellite data.
The research activities of this grant are related to the development of novel methodologies based on artificial intelligence and deep learning for the automatic analysis of time series of multisensor images acquired by Earth Observation satellites. The research will be focused on the problems of automatic classification (semantic segmentation),  change detection in multitemporal images and analysis of long image time series.  The activity will consider methodological research (for the development of novel methods) and the related application to real-world scenarios.

(6N)  Development of an anechoic chamber digital twin for the prediction of antennas for space applications radiation measurements

Funding institution: Thales Alenia Space
Doctoral site:  University of Trento
Contact: Prof. Leonardo Lizzi [leonardo.lizzi [at] unitn.it]
Funds: Own funds
Mobility abroad: compulsory, minimum 6 months
Periods in companies/research centres/public administrations: Optional

An anechoic chamber is an isolated environment structured in such a way as to reduce as much as possible the reflection of electromagnetic (EM) waves on the walls. In the framework of space applications, such a piece of equipment is crucial for radiofrequency (RF) testing of satellite and spacecraft devices without the influence of disturbing and unwanted signals (e.g., those generated by cell phones, radars, and other radio frequency emitters). To reduce the risk of the test activities, it would be useful to have a digital twin of the anechoic chamber that could be used to design and optimize the test set-up as well as to predict the behaviour of the test results. Within this PhD, the candidate will develop, with the help of EM high-frequency simulation tools, a numerical model of an anechoic chamber. This model will be used to predict the results of the test carried out on a satellite device, (usually called EUT, equipment under test). The focus will be on the measurement of the radiation properties of antennas for space applications. However, additional types of tests and devices could also be considered. To validate the model, several antennas/EUTs, characterized by different EM properties (e.g., frequency of operation, radiation behaviour, etc.) will be simulated, realized, and tested. The model will be also used to quantify the effect on the test results of chamber non-idealities (e.g., floor EM properties, absorbers, doors, etc.). The candidate should hold a master’s degree in electronic engineering, telecommunication engineering or equivalent. The knowledge of EM simulation tools such as CST or HFSS will be considered a plus.