DC1 (hosted by and enrolled in the Doctoral Program at the Aristotle University of Thessaloniki)

Contract Duration: 36 months

PhD Title: Design and optimisation of metasurface-based sensors for environmental monitoring

Description: The goal is to create sensor prototypes using space-time modulated metasurfaces for real-time environmental monitoring, optimizing design for sensitivity, accuracy, and reliability. This involves exploring materials, assessing electromagnetic properties, and compensating for fabrication imperfections and manufacturing tolerances using polynomial chaos, stochastic methods, and AI. Rigorous testing will assess sensor performance under factors like temperature and humidity. Integration into environmental monitoring systems will be pursued, ensuring compatibility. Field tests will validate effectiveness in real scenarios, comparing with conventional sensors. The research will optimize power consumption, develop analysis algorithms, explore cost-effective fabrication, and assess scalability. The study will also conduct an environmental impact assessment for a holistic approach to research objectives.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Greece for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Greece.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Both the Bachelor's and Master's Degrees must be awarded by academic institutions officially recognized by the Hellenic National Academic Recognition and Information Centre (Hellenic NARIC, see link: https://www.doatap.gr/home_english/organization_english/). Official recognition is automatically granted if the Degrees have been awarded by academic institutions listed in the following Hellenic NARIC registry: https://www.doatap.gr/anagnorish/ethniko-mitroo-anagnorismenon-idrymaton-anotatis-ekpaidefsis-tis-allodapis/ . If the awarding institution of either the Bachelor's or Master's Degree (or both) is not included in the aforementioned registry, an official recognition certificate for the respective Degree(s) is required from Hellenic NARIC.
6.    Knowledge of metasurface modelling using HFSS or CST is necessary.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    Official recognition certificate from the Hellenic NARIC for each Degree, if the respective awarding institution is not listed in the aforementioned Hellenic NARIC registry.
9.    A copy of the Master’s thesis.
10.    At least two recommendation letters.
11.    Certificate of English language proficiency.
12.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a single ZIP file to Dr. Zaharias Zaharis via email at zaharis@auth.gr

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DC2 (hosted by and enrolled in the Doctoral Program at the Aristotle University of Thessaloniki)

Contract Duration: 36 months

PhD Title: Improved radar systems based on frequency selective surfaces
Description: The research aims to enhance radar systems using innovative frequency selective surfaces (FSS) based on space-time modulated metamaterials. Objectives include designing FSS for radar applications, improving sensitivity, accuracy, and signal-to-noise ratios. Focus areas include adaptability to diverse environments, seamless integration with existing radar tech, and energy-efficient mechanisms for reduced power consumption. Advanced ML/DL algorithms optimize real-time data processing. Reliability testing ensures functionality under various conditions. The study explores cost-effective fabrication and assesses scalability. Compensation for imperfections will be considered using polynomial chaos, stochastic time-domain methodologies, and AI algorithms. Validation includes simulations and real-world tests, with findings disseminated through publications and conferences, benefiting the scientific community and radar technology stakeholders.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Greece for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Greece.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Both the Bachelor's and Master's Degrees must be awarded by academic institutions officially recognized by the Hellenic National Academic Recognition and Information Centre (Hellenic NARIC, see link: https://www.doatap.gr/home_english/organization_english/). Official recognition is automatically granted if the Degrees have been awarded by academic institutions listed in the following Hellenic NARIC registry: https://www.doatap.gr/anagnorish/ethniko-mitroo-anagnorismenon-idrymaton-anotatis-ekpaidefsis-tis-allodapis/ . If the awarding institution of either the Bachelor's or Master's Degree (or both) is not included in the aforementioned registry, an official recognition certificate for the respective Degree(s) is required from Hellenic NARIC.
6.    Knowledge of metasurface modelling using HFSS or CST is necessary.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    Official recognition certificate from the Hellenic NARIC for each Degree, if the respective awarding institution is not listed in the aforementioned Hellenic NARIC registry.
9.    A copy of the Master’s thesis.
10.    At least two recommendation letters.
11.    Certificate of English language proficiency.
12.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a single ZIP file to Dr. Zaharias Zaharis via email at zaharis@auth.gr

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DC3 (hosted by and enrolled in the Doctoral Program at the International Hellenic University)

Contract Duration: 36 months

PhD Title: Multi-link sensing and communication in WLANs

Description: The research aims to advance contemporary sensing and communication techniques and protocols in the context of wireless local area networks with emphasis on (but not restricted to) IEEE 802.11 future deployments. The main objectives are related to the exploitation of multi-link functionality and operation to provide sensing and communication at multiple operating frequencies that are envisioned for next-generation Wi-Fi systems, e.g., 2.4, 5, 6, and 60 GHz. The study will focus on enhancements in the context of medium access control, physical layer, or access point coordination and resource allocation of multi-link operation to support sensing and communication KPIs while preserving energy efficiency. In addition, techniques related to the creation and use of channel knowledge maps (CKM) will be investigated to reduce CSI transfer and drive fast decisions at the communication level to facilitate low-latency and high-reliability environment-aware services.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Greece for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Greece.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Both the Bachelor's and Master's Degrees must be awarded by academic institutions officially recognized by the Hellenic National Academic Recognition and Information Centre (Hellenic NARIC, see link: https://www.doatap.gr/home_english/organization_english/). Official recognition is automatically granted if the Degrees have been awarded by academic institutions listed in the following Hellenic NARIC registry: https://www.doatap.gr/anagnorish/ethniko-mitroo-anagnorismenon-idrymaton-anotatis-ekpaidefsis-tis-allodapis/ . If the awarding institution of either the Bachelor's or Master's Degree (or both) is not included in the aforementioned registry, an official recognition certificate for the respective Degree(s) is required from Hellenic NARIC.
6.    Knowledge of wireless communications.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    Official recognition certificate from the Hellenic NARIC for each Degree, if the respective awarding institution is not listed in the aforementioned Hellenic NARIC registry.
9.    A copy of the Master’s thesis.
10.    At least two recommendation letters.
11.    Certificate of English language proficiency.
12.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a single ZIP file to Prof. Periklis Chatzimisios and Prof. Athanasios Iossifides (Iosifidis) via email at pchatzimisios@ihu.gr and aiosifidis@ihu.gr 

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DC4 (hosted by SmartAvatar B.V. and enrolled in the Doctoral Program at the Technical University of Sofia)

Contract Duration: 36 months

PhD Title: Digital cyber twin for cooperative 6G environments

Description: The research aims to design capabilities of real-time DTs to enable the trustworthy and reliable collection of data from millions of sensors in support of smart system optimisation, and also to demonstrate a PoC implementation of the digital cyber twin and its real-time responsiveness. To ensure that sensor data communications with the DT have not been tampered with and that the compute process is secure, a Zero Trust Data security model is proposed. A PoC for a Zero Trust DT architecture will be realised that would demonstrate the following features: (i) protect every sensor message with a different encryption key as a countermeasure to interception and tampering; (ii) process sensitive data within the DT without the risk of leaking information; (iii) transmit control messages to smart transportation and energy systems using a dynamically provisioned encrypted message.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in the Netherlands for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside the Netherlands.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Knowledge of cloud computing (AWS, Azure, Google Cloud) and container orchestration (Kubernetes, Docker); Hands-on experience with IoT security, real-time data streaming (Kafka, MQTT, RabbitMQ), and cryptographic techniques; Strong programming skills in Python, Java, Go, C#, or Rust; Understanding of Zero Trust security models, authentication, and encryption; Experience in blockchain, secure federated learning, or confidential computing; research experience with published work in cybersecurity, AI, or distributed computing.is necessary.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master’s Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    A copy of the Master’s thesis.
9.    At least two recommendation letters.
10.    Certificate of English language proficiency.
11.    Copies of publications (if any) in scientific journals and conference proceedings.
12.    If selected an Apostille certification of the Master degree issued outside of the EU will be required.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a single ZIP file to Dr. Albena Mihovska and Dr. Neeli Prasad via email at albena.mihovska@smartavatar.nl and neeli.prasad@smartavatar.nl
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DC5 (hosted by Acceligence Ltd. and enrolled in the Doctoral Program at the Aristotle University of Thessaloniki)

Contract Duration: 36 months

PhD Title: Metasurface-based reconfigurable antenna array for target recognition and tracking

Description: The research aims for an advanced intelligent sensing system, integrating reconfigurable antennas with space-time metasurface technology. Objectives include optimizing antennas for enhanced beamforming, frequency agility, and target recognition in dynamic environments. ML/DL algorithms will identify multiple targets in real-time, adapting to changing dynamics. Experimental validation will assess system performance, with findings shared through scholarly outlets for insights in intelligent sensing and target recognition.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Cyprus for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Cyprus.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Both the Bachelor's and Master's Degrees must be awarded by academic institutions officially recognized by the Hellenic National Academic Recognition and Information Centre (Hellenic NARIC, see link: https://www.doatap.gr/home_english/organization_english/). Official recognition is automatically granted if the Degrees have been awarded by academic institutions listed in the following Hellenic NARIC registry: https://www.doatap.gr/anagnorish/ethniko-mitroo-anagnorismenon-idrymaton-anotatis-ekpaidefsis-tis-allodapis/ . If the awarding institution of either the Bachelor's or Master's Degree (or both) is not included in the aforementioned registry, an official recognition certificate for the respective Degree(s) is required from Hellenic NARIC.
6.    Knowledge of machine learning and metasurface modelling using HFSS or CST is necessary.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    Official recognition certificate from the Hellenic NARIC for each Degree, if the respective awarding institution is not listed in the aforementioned registry.
9.    A copy of the Master’s thesis.
10.    At least two recommendation letters.
11.    Certificate of English language proficiency.
12.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a single ZIP file to Dr. Pantelis Velanas via email at pvelanas@accelligence.tech

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DC6 (hosted by Italtel S.p.A. and enrolled in the Doctoral Program at the Aristotle University of Thessaloniki)

Contract Duration: 36 months

PhD Title: Metasurface-enhanced smart sensor networks for environmental threat detection

Description: The research targets metasurface-enhanced smart sensor networks for precise environmental threat detection. Objectives include designing intelligent sensor nodes using metasurface tech to enhance sensitivity and selectivity in detecting environmental threats. The study focuses on integrating metasurface-based sensors into dynamic networks for real-time data analysis. Advanced ML/DL algorithms improve threat detection accuracy. The research also explores energy-efficient communication protocols for optimal performance in remote environments.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Italy for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Italy.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Both the Bachelor's and Master's Degrees must be awarded by academic institutions officially recognized by the Hellenic National Academic Recognition and Information Centre (Hellenic NARIC, see link: https://www.doatap.gr/home_english/organization_english/). Official recognition is automatically granted if the Degrees have been awarded by academic institutions listed in the following Hellenic NARIC registry: https://www.doatap.gr/anagnorish/ethniko-mitroo-anagnorismenon-idrymaton-anotatis-ekpaidefsis-tis-allodapis/ . If the awarding institution of either the Bachelor's or Master's Degree (or both) is not included in the aforementioned registry, an official recognition certificate for the respective Degree(s) is required from Hellenic NARIC.
6.    Knowledge of machine learning and metasurface modelling using HFSS or CST is necessary.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    Official recognition certificate from the Hellenic NARIC for each Degree, if the respective awarding institution is not listed in the aforementioned Hellenic NARIC registry.
9.    A copy of the Master’s thesis.
10.    At least two recommendation letters.
11.    Certificate of English language proficiency.
12.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a ZIP file to Mr. Antonino Albanese via email at antonino.albanese@italtel.com
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DC7 (hosted by and enrolled in the Doctoral Program at Universidad Carlos III de Madrid)

Contract Duration: 36 months

PhD Title: Dual monostatic-bistatic mobile integrated localisation and communication design

Description: The main objectives are the design of low complexity and high resolution AI-enhanced dual monostatic - bistatic systems that could be used in mobile scenarios working simultaneously as monostatic and bistatic. To develop the signal processing associated to leverage on the dual working strategy to reduce complexity locally and improve robustness and resolution. To develop intelligent cooperative solutions and interference cancellation algorithms for obtaining better performance than current monostatic or bistatic ISAC systems. To enhance by using Machine Learning (ML) technique the performance and the resolution. To explore the use of ML for managing interference and complex environments. The research anticipates an inflexion point in the design of either monostatic and bistatic ISAC systems with the application of dual signals to avoid disadvantages and pain points of both designs and leverage the advantages of both worlds at the same time. Since complexity is going to be a key parameter, design for light terminals (mobility), some of the experience and results obtained in this research are likely to be very useful for other designs. Robust yet flexible algorithms for dual monostatic-bistatic designs are expected. Their enhanced performance is going to be validated through both theoretical analysis and simulations. Some of them are planned to be implemented in the demonstrator for final results.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Spain for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Spain.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Both the Bachelor's and Master's degrees must be awarded by an academic institution officially recognized by the Spanish government, provided that at least 300 ECTS credits have been passed in these two cycles as a whole, with at least 60 ECTS being from the Master's level
6.    Knowledge of wireless communications physical layer techniques, signal processing, and machine learning is necessary.
7.    Proficiency in programming and simulating wireless communication systems, especially with Matlab and/or Python.

Applicants are required to submit the following documents:
1.    Curriculum Vitae (CV).
2.    Letter of motivation.
3.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
4.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
5.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
6.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
7.    At least two recommendation letters.
8.    Certificate of English language proficiency.
9.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted using the following online Form:
https://aplicaciones.uc3m.es/formulario/ISACNEWTONForm

If you find any problem submitting the form above, please send an email to Prof. Víctor P. Gil Jiménez at: isac-newton@tsc.uc3m.es
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DC8 (hosted by and enrolled in the Doctoral Program at Universidad Carlos III de Madrid)

Contract Duration: 36 months

PhD Title: Machine learning as enabler of compact and flexible ISAC designs

Description: The primary objectives include exploring and applying appropriate ML techniques for designing compact ISAC systems based on 5G signals and other emerging waveforms anticipated for 6G. Additionally, leveraging ML for the design of novel and adaptable waveforms capable of addressing both communication and sensing requirements. Finally, developing dynamic algorithms based on ML techniques to address various scenarios. The research aims to develop algorithms that are simultaneously flexible and of low complexity to enhance current designs. Given the emphasis on flexibility as a key design approach, these algorithms should adapt to diverse scenarios and use cases, outperforming current designs tailored for specific scenarios and demonstrating improved performance in varying conditions. The study envisions multiple use cases with applied ML techniques, expecting validation through extensive simulations. Furthermore, the research anticipates providing guidelines for applying these techniques to other use cases and scenarios. The most promising techniques identified will be implemented in a demonstrator.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Spain for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Spain.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Both the Bachelor's and Master's degrees must be awarded by an academic institution officially recognized by the Spanish government, provided that at least 300 ECTS credits have been passed in these two cycles as a whole, with at least 60 ECTS being from the Master's level
6.    Knowledge of wireless communications physical layer techniques, signal processing, and machine learning is necessary.
7.    Proficiency in programming and simulating wireless communication systems, especially with Matlab and/or Python.

Applicants are required to submit the following documents:
1.    Curriculum Vitae (CV).
2.    Letter of motivation.
3.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
4.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
5.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
6.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
7.    At least two recommendation letters.
8.    Certificate of English language proficiency.
9.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted using the following online Form:
https://aplicaciones.uc3m.es/formulario/ISACNEWTONForm 

If you find any problem submitting the form above, please send an email to Prof. Víctor P. Gil Jiménez at: isac-newton@tsc.uc3m.es
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DC9 (hosted by and enrolled in the Doctoral Program at Technische Universität Wien)

Contract Duration: 36 months

PhD Title: ML-enhanced distributed sensing and communication in multi-RIS augmented wireless propagation environments

Description: The objective of this research project is to enhance communication and sensing capabilities in multi-RIS augmented wireless propagation environments by applying advanced machine learning (ML)-based signal processing techniques. Single RIS deployments, constrained by coarse phase quantisation and limited observation coverage, provide limited support for sensing applications. However, fusing even coarse observations from multiple distributed RISs has the potential to provide remarkably accurate and robust sensing capabilities, even in non-line-of-sight propagation scenarios. The primary objective of this research is to harness the power of multi-RIS augmented ISAC systems by integrating ML-enhanced signal processing methods to combine sensing data from base stations with complementary information from the RISs, such as their optimised phase configurations. This research focuses on ultra-wideband transmissions, considering the frequency-selective nature of real-world RIS responses, which provide high temporal resolution. It will also explore the latest technological advances in RIS, including non-diagonal RIS and STAR-RIS. The project also targets high-mobility scenarios in vehicular and UAV-based networks, addressing the unique challenges posed by these dynamic environments.

Eligibility Requirements:
•    The candidate must not have been awarded a PhD Degree.
•    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
•    Candidates must not have resided in Austria for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Austria.
•    Proficiency in written and spoken English is required and must be formally demonstrated.
•    Knowledge of scientific work methods and interest in academic research and teaching.
•    Expertise in one or more of the following disciplines: Telecommunications, Machine Learning, Signal Processing, Mathematical Optimization.
•    Proficiency in programming and simulating wireless communication systems, especially with Matlab and/or Python.
•    Teamwork, problem-solving skills, and innovation capability.
 

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    A copy of the Master’s thesis.
9.    At least two recommendation letters.
10.    Certificate of English language proficiency.
11.    Copies of publications (if any) in scientific journals and conference proceedings.
12.    Any relevant extracurricular certificates demonstrating proficiency in programming languages, as well as prior experience in wireless communications, signal processing, and machine learning.

Submission Deadline: April 10, 2025

Applications for this position must be uploaded as a single ZIP file, using the naming convention firstname_lastname.zip, at: https://owncloud.tuwien.ac.at/index.php/s/GB82lHp8WMc1D4j
Additionally, applicants should send an email containing only a brief cover letter, without any attachments, to Prof. Stefan Schwarz: stefan.schwarz (at) tuwien (dot) ac (dot) at
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DC10 (hosted by Silicon Austria Labs GmbH and enrolled in the Doctoral Program at Technische Universität Wien)

Contract Duration: 36 months

PhD Title: Localisation and situational awareness for high reliability in integrated sensing and communication 6G networks

Description: This research topic aims to develop prediction and situational awareness algorithms with high accuracy tailored for industrial environments. Through the joint utilization of sensing and communication data, the study will offer various enhancements, including reliable localization and sensing techniques, obstacle detection and avoidance, and advanced machine learning-driven predictive algorithms. 
A key focus will be on forecasting communication properties over a given future time-frame. By analyzing real-time sensing data and network conditions, the research will enable proactive decision-making, including predicting potential communication degradation, optimizing operational adjustments, and dynamically recommending speed or path modifications. This work will contribute to more efficient and resilient industrial automation and connectivity.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Austria for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Austria.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Knowledge of scientific work methods and interest in academic research and teaching.
6.    Expertise in one or more of the following disciplines: Telecommunications, Machine Learning, Signal Processing, Mathematical Optimization.
7.    Proficiency in programming and simulating wireless communication systems, especially with Matlab and/or Python.
8.    Teamwork, problem-solving skills, and innovation capability.

Applicants are required to submit the following documents:
1.    Curriculum Vitae (CV).
2.    Letter of motivation.
3.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
4.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
5.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
6.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
7.    A copy of the Master’s thesis.
8.    At least two recommendation letters.
9.    Certificate of English language proficiency.
10.    Copies of publications (if any) in scientific journals and conference proceedings.
11.    Any relevant extracurricular certificates demonstrating proficiency in programming languages, as well as prior experience in wireless communications, signal processing, and machine learning.

Submission Deadline: April 10, 2025

Applications for this position must be submitted at https://silicon-austria-labs.jobs.personio.de/job/2019425
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DC11 (hosted by and enrolled in the Doctoral Program at Technische Universität Berlin)

Contract Duration: 36 months

PhD Title: Seamless user-centric random access, cluster formation, channel estimation, and multistatic sensing in cell-free massive MIMO (CF-mMIMO) networks
Description: This research aims to explore unsourced random access (uRA) within a user-centric cell-free massive MIMO (CF-mMIMO) network, developing novel distributed sparse estimation techniques to address compressed sensing challenges. It will also characterise the achievable rates for short-block communication by analysing the trade-off between rate and probability of error using a finite block length framework. The study further investigates fairness scheduling in scenarios where the number of users significantly exceeds the spatial multiplexing gain of the system. Additionally, it focuses on optimising edge computing resource allocation by strategically placing user-centric cluster processors as software-defined network functions hosted in the distributed units (DUs) and optimising data routing through the fronthaul to minimise network load. This research is at the forefront of 6G wireless technology and involves advanced mathematical optimization, information theoretic and coding theoretic concepts, and possibly applications of deep learning to the physical layer.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, Applied Mathematics, or a related field.
3.    Candidates must not have resided in Germany for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Germany.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    A solid background in statistical signal processing, mathematical optimization, wireless communications (modeling, simulation, general physical layer communication theoretic approaches) is highly desirable. A master-level background in information theory and channel coding is a plus.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    A copy of the Master’s thesis.
9.    At least two recommendation letters.
10.    Certificate of English language proficiency.
11.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a single ZIP file to Prof. Giuseppe Caire via email at caire@tu-berlin.de and in cc to Ms. Jana Hantke (email: jana.hantke@tu-berlin.de )
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DC12 (hosted by and enrolled in the Doctoral Program at the Technical University of Sofia)

Contract Duration: 36 months

PhD Title: ML-empowered RAN

Description: This research focuses on developing and implementing intelligent O-RAN intelligent controller (RIC) functionalities for both non-real-time (non-RT) and near-real-time (near-RT) responses. It aims to design and integrate Distributed Applications (dApps) within the non-RT and near-RT RIC, as well as to develop AI-driven solutions for real-time radio access network (RAN) functionalities. The expected outcomes include the implementation of O-RAN functionalities within a testbed platform, incorporating non-RT RIC, near-RT RIC, and dApps. By deploying dApps directly within centralised and distributed units (CUs and DUs), the system will leverage low-level data metrics—such as MAC/PHY-level key performance metrics (KPMs), transmission queues, and beam directionality—to enable AI-driven real-time RAN functions. These functionalities will include beamforming, user scheduling, puncturing, interference management, and modulation management. Additionally, machine learning models will be designed as independent internal applications and deployed within the controllers, allowing their application across various use cases.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Bulgaria for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Bulgaria.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Expertise in one or more of the following disciplines: Telecommunications, Wireless Networks, Signal Processing, Mathematical Optimization.
6.    Proficiency in programming and simulations, especially with Matlab, C, C++ or Python.
7.    Familiar with ML frameworks & libraries.
8.    Knowledge of scientific work methods and research.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    A copy of the Master’s thesis.
9.    At least two recommendation letters.
10.    Certificate of English language proficiency.
11.    Copies of publications (if any) in scientific journals and conference proceedings.
12.    If selected an Apostille certification of the Master degree issued outside of the EU will be required.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a single ZIP file to Prof. Vladimir Poulkov via email at vkp@tu-sofia.bg 

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DC13 (hosted by GMV Aerospace and Defence S.A. and enrolled in the Doctoral Program at Universidad Carlos III de Madrid)

Contract Duration: 36 months

PhD Title: Remote sensing and interference identification in NTN 5G signals

Description: This research aims to optimise network and resource management in 5G Non-Terrestrial Networks (NTN) by developing advanced algorithms tailored to these environments. The expected outcomes include solutions compatible with various payload architectures, ranging from transparent to fully regenerative systems. Anticipated results involve the creation of novel machine learning-based algorithms for real-time system evaluation and dynamic resource planning. Additionally, a proof-of-concept (PoC) or demonstrator will be developed, with a strong focus on solutions leveraging DVB-S2 and 5G technologies.

Eligibility Requirements:

1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in Spain for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Spain.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Both the Bachelor's and Master's degrees must be awarded by an academic institution officially recognized by the Spanish government, provided that at least 300 ECTS credits have been passed in these two cycles as a whole, with at least 60 ECTS being from the Master's level.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    A copy of the Master’s thesis.
9.    At least two recommendation letters.
10.    Certificate of English language proficiency.
11.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a ZIP file to Ms. María Ángeles Pérez González via email at spcs@gmv.com

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DC14 (hosted by and enrolled in the Doctoral Program at the University of Huddersfield)

Contract Duration: 36 months

PhD Title: Through-wall imaging using metasurface antenna arrays

Description: The research aims to revolutionize through-wall imaging with advanced metasurface antennas for efficient wave manipulation. Objectives include designing high-performance arrays, optimizing parameters, ensuring adaptability, real-time imaging, and ethical considerations. Documentation and dissemination will contribute to understanding through-wall imaging, impacting both science and applications.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in the UK for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside the UK.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Knowledge of machine learning and antenna/metasurface modelling using CST is necessary.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    A copy of the Master’s thesis.
9.    At least two recommendation letters.
10.    Certificate of English language proficiency.
11.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a ZIP file to Prof. Pavlos Lazaridis via email at p.lazaridis@hud.ac.uk
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DC15 (hosted by and enrolled in the Doctoral Program at the University of Huddersfield)

Contract Duration: 36 months

PhD Title: Metasurface-enabled synthetic aperture radar installed on UAVs

Description: The research aims to advance radar technology by integrating metasurface-enabled synthetic aperture radar (SAR) with ML/DL algorithms on UAVs. Objectives include optimising metasurfaces for efficient electromagnetic wave manipulation, integrating with UAVs or stability and power efficiency, and using ML/DL algorithms to enhance SAR resolution for accurate target detection and classification. The study focuses on adapting systems to dynamic environments, real-time processing, and autonomous operation, emphasizing energy efficiency. Field trials and simulations will validate system performance, contributing to radar technology and UAV applications.

Eligibility Requirements:
1.    The candidate must not have been awarded a PhD Degree.
2.    A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3.    Candidates must not have resided in the UK for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside the UK.
4.    Proficiency in written and spoken English is required and must be formally demonstrated.
5.    Knowledge of machine learning and antenna/metasurface modelling using CST is necessary.

Applicants are required to submit the following documents:
1.    Application Form
2.    Curriculum Vitae (CV).
3.    Letter of motivation.
4.    Certificate(s) of Bachelor's Degree(s), with an official English translation if issued in a different language.
5.    Academic transcripts for undergraduate studies, with official English translations if issued in a different language.
6.    Certificate(s) of Master's Degree(s), with an official English translation if issued in a different language.
7.    Academic transcripts for postgraduate studies, with official English translations if issued in a different language.
8.    A copy of the Master’s thesis.
9.    At least two recommendation letters.
10.    Certificate of English language proficiency.
11.    Copies of publications (if any) in scientific journals and conference proceedings.

Submission Deadline: April 10, 2025

Applications for this position must be submitted as a ZIP file to Prof. Pavlos Lazaridis via email at p.lazaridis@hud.ac.uk
 

ISAC-NEWTON will provide the DCs with a unique, advanced, multi-disciplinary training programme covering all aspects of the ISAC science field: modelling, design, development, data analysis, validation and translation to the application. ISAC-NEWTON will offer scientific excellence and research management training activities to researchers, including research proposal management and key transferable skills (e.g., scientific outreach, entrepreneurship, technology transfer, training about standardisation, ethical issues – including diversity, equity, and inclusion etc.), while addressing research excellence as a multidimensional concept in the main research area of the DN. The training plans include 2 seasonal schools (SS), 2 scientific workshops (SW), 4 capacity building workshops (CW), 2 scientific conferences (SC), 6 training sessions (T) for supervisors, and 12 hours of MOOCs on ISAC technologies and techniques. These will be complemented with mobility activities planned as secondments, allowing for the establishment of networking structures and increasing the internationalisation of exposure for the DCs.

•    Access to state-of-the-art research facilities and resources.
•    Opportunities for international travel and collaboration.
•    Participation in international conferences.
•    A stimulating and supportive research environment.
•    The salary consists of the gross Monthly Living Allowance of 3.400,00 EUR per month pondered by the EU correction coefficient (specific for the countries where the hosting Institutions are located). In addition, a Mobility Allowance of 600,00 EUR per month will be paid, and also possibly another 660,00 EUR per month of Family Allowance depending on marital status.The DC salary is subject to local tax, employee's and employer's social contributions, and other deductions following national regulations.
 

Based on a scoring system that takes into account (1) the applicant’s marks during Bachelor/Master training, (2) work and research experience, (3) recommendation letters, (4) English fluency (according to the TOEFL or IELTS test), and (5) the motivation of the candidate, a priority list of candidates will be established. Candidates with the highest scores will be selected for interview, which will further ensure that high quality applicants are selected for all 15 positions.