iPhD Student Position on “Advanced Antenna Array Synthesis Methodologies"

Prestigious industrial PhD Student Position on “Advanced Antenna Array Synthesis Methodologies”. Department of Research and Development, The Antenna Company EM Group, Department of Electrical Engineering, Eindhoven University of Technology

Irène Curie Fellowship

No

Department(s)

Electrical Engineering

Reference number

V36.7202

Communication networks provide the bedrock for digital transition of our society and economy.
In 4G and 5G mobile networks, the Netherlands is strong in RF semiconductor technologies and applications of mobile technology. 6G, the new generation for the 2030s, offers large economic opportunities for the Netherlands to extend this position to areas in the global 6G value chain that have earlier moved to Asian and US companies. Securing such a position is crucial for the Netherlands to stay in control of its mobile networks. In the Future Network Services (FNS) program, leading ICT- and semiconductor companies and research institutions will jointly research specific parts of 6G: software antennas, AI-driven network software and leading 6G applications. By integrating these parts at the 6G software layer, FNS creates a powerful approach to make 6G a truly intelligent network. This innovation gives an important impulse to the Dutch economy and sustainable earning power, through advanced industrial activity and significant export opportunities. It will make 6G networks more energy efficient and drive digital autonomy.

Outline of the FNS-6G program:

The FNS innovations are developed in four program lines: (1) intelligent components, developing software antennas for the new high (mm-wave and THz) frequencies in 6G; (2) intelligent networks, developing AI-driven software for 6G radio and core networks; (3) leading applications, developing new 6G applications in mobility, energy, health and other sectors that create value through new set- ups of the sector value chains; (4) ecosystem strengthening, integrating the FNS innovations in the national 6G testbed, stimulating start-ups and SMEs, developing and executing the human capital agenda and ensuring policy alignment. The consortium currently consists of a mix of 60 large and small telecom, semiconductor and ICT companies, universities and public bodies:

• PL1: TU/e (lead), Aircision, Altum-RF, Ampleon, AntenneX, Astron, Bosch (ItoM), Chalmers, CITC, Ericsson, IMEC, KPN, NXP, PITC, Prodrive, RobinRadar, Sabic, Signify, TheAntennaCompany, TNO, TUDelft, Twente University (UT), Viasat, VodafoneZiggo, VTEC.
• PL2: TUDelft (lead), Almende, AMS-IX, Ericsson, IS-Wireless, KPN, Nokia, NVIDIA, Solvinity, SURF, TNO, TU/e, Universiteit van Amsterdam, UT, Viasat, VodafoneZiggo, Vrije Universiteit (Amsterdam).
• PL3: TNO (lead), Alliander, ASML, Comforest, Cordis, Drone Delivery Service, Ericsson, Future Mobility Network, gemeente Amsterdam and Rotterdam, Gomibo, KPN, Philips, Port Of Rotterdam, PWXR, Robin Radar, TenneT TSO, T-Mobile, Vialis.
• PL4: TUDelft (lead), BTG, Ericsson, ECP, EZK, Hanze Hogeschool, KOREWireless, KPN, Liberty Global, Nokia, OostNL, RDI, SURF, TU/e, T-Mobile , UT, Vodafone, Ziggo.

PhD position on “Advanced Antenna Array Synthesis Methodologies”:

The research program focuses on advanced deterministic synthesis techniques for antenna arrays. These techniques address the complex, multidimensional, and nonlinear problem of antenna array pattern synthesis, offering advantages over traditional metaheuristic methods like genetic algorithms and particle swarm optimization. The deterministic approach, characterized by lower computational complexity and higher efficiency, involves evaluating the location and excitation coefficients of antenna elements while adhering to design constraints. The incorporation of AI enhances these techniques, allowing for more efficient handling of complex design requirements and constraints. This synergy between deterministic methods and AI is expected to lead to more effective and efficient antenna array designs, outperforming evolutionary methods in terms of speed, computational load, and possibly accuracy in conforming to design specifications. This research program would explore these advantages in depth, developing and validating new algorithms for antenna array synthesis that leverage the strengths of both deterministic methods and AI with an emphasis on the following aspects:

• Advanced Deterministic Synthesis Techniques: Investigating novel deterministic methods for antenna array synthesis, such as advanced iterative Fourier transform approaches, and exploring their computational efficiency and effectiveness in meeting assigned performance criteria.
• Integration with AI and Machine Learning: Examining how artificial intelligence (AI) and machine learning algorithms can be integrated with deterministic synthesis techniques to optimize antenna array design. This could involve developing AI-driven models to automate the synthesis process, enhance design accuracy, and reduce computational time.
• Comparison with Evolutionary Methodologies: Conducting comparative studies to assess the advantages of deterministic synthesis techniques over evolutionary methods, such as genetic algorithms, in terms of accuracy, speed, and reliability. This comparison can highlight the scenarios where deterministic methods are more suitable.
• Application in Emerging Technologies: Applying deterministic synthesis methods to design antenna arrays for emerging technologies like 5G and beyond, considering aspects like millimeter-wave communications, beamforming, and spatial filtering.
• CAD Tool Development: Developing sophisticated computer-aided design tools that incorporate deterministic synthesis algorithms to assist designers in creating efficient antenna arrays for various applications, including wireless communications and remote sensing.

This research program aims to push the boundaries of antenna array design by leveraging the precision and efficiency of deterministic methods, enhanced by AI, to meet the evolving demands of modern wireless communication systems.

• Applicants should have, or expect to receive, a Master of Science degree or equivalent in a relevant electrical engineering or applied physics discipline.
• The selection is based on the candidates’ application documents in combination with their performance during the interviews and possible assignments.
• Besides good subject knowledge, emphasis will be placed on creative thinking, motivation, ability to work in a team, initiative to work independently and personal suitability for research training.
• An educational background in the areas of electromagnetic field theory, antenna design, antenna arrays, microwave engineering, and signal processing is preferred. Practical experience is considered beneficial.
• Proficiency in using scientific and engineering software packages such as CST Studio Suite, Python, Matlab, Mathematica, etc. are advantageous.
• Fluency in spoken and written English is essential.

• An opportunity for a significant role in a rapidly evolving scale-up within the advanced antenna systems sector, offering exposure to both the scientific and industrial communities.
• Four years of full-time employment, featuring biannual performance and progress review cycles.
• Complimentary access to facilities of The Antenna Company to facilitate your PhD research, with annual discussions on personal development programs.
• A competitive starting gross monthly salary of €3,355 (based on full-time employment), with meaningful annual increases reflecting performance and results, in line with the salary policies of The Antenna Company.
• An additional annual holiday bonus amounting to 8% of your yearly gross salary.
• A comprehensive package of fringe benefits, including access to state-of-the-art technical infrastructure, reimbursement of commuting expenses, company mobile phone, and a pension plan, is provided according to the policies of The Antenna Company.

This vacancy concerns a partnership of which TU/e is one of the participating parties. Employment will be with The Antenna Company.

Further information can be obtained by using the following contact addresses:
Dr. Diego Caratelli (diego.caratelli[at]antennacompany , d.caratelli[at]tue.nl )  and Prof. Bart Smolders (a.b.smolders[at]tue.nl ).