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Samel Arslanagić

11 months ago

PhD in Machine Learning-Aided Design of Antennas and Metasurfaces for Efficient Electromagnetic Wave Interaction with Lossy Materials Technical University of Denmark in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Denmark

University

Technical University of Denmark

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Keywords

Computer Science
Biomedical Engineering
Electrical Engineering
Electrical Properties
Cell Culture Techniques
Biomedical Applications
Experimental
Metasurface
Machinelearning
Electromagnetics
Tissue
Simulation Models
In Vivo Sensing

About this position

This PhD position at the Technical University of Denmark (DTU) offers an exciting opportunity to advance the field of electromagnetic wave interaction with lossy materials, such as human tissue, through the innovative use of machine learning in the design of antennas and metasurfaces. The project is a collaborative initiative between DTU Space and DTU Electro, with industrial benchmarking support from HHC Medical. The research will focus on the theoretical, numerical, and experimental aspects of machine learning-assisted design for efficient propagation and focusing of electromagnetic waves in various lossy media, including in vitro sensing of biological samples.

As a PhD student, you will engage in a range of activities, including microwave measurements of dielectric properties, development of simulation models for electromagnetic wave interaction, machine learning-based design of antennas and metasurfaces, experimental validation of near-field interactions, and prototype fabrication and assessment. The project aims to connect electromagnetic performance with biological outcomes, leveraging benchmarking by HHC Medical using biological assays.

The position offers a unique chance to develop expertise in antennas and metasurfaces for biomedical applications, machine learning techniques for electromagnetic device design, and advanced measurement techniques. You will benefit from close collaboration with leading research groups at DTU and interaction with industrial partners. The PhD program includes 30 ECTS of tailored coursework, covering both technical and soft skills, and provides a supportive international research environment.

Applicants should have a strong background in electromagnetics and antennas, with solid knowledge of metasurfaces and preferably experience in machine learning. Experimental skills and familiarity with applications of machine learning in electromagnetics are advantageous. A two-year master's degree (120 ECTS) or equivalent is required. Proficiency in English is essential. The position is fully funded for 3 years, with salary and terms based on the Danish Confederation of Professional Associations' agreement.

To apply, submit your complete application online by 19 December 2025, including a cover letter, CV, grade transcripts, and diplomas in English as a single PDF file. For more information about the research environment, visit the DTU Space and DTU Electro websites. DTU is committed to diversity and encourages applications from all qualified candidates, regardless of background.

Funding details

Available

What's required

Applicants must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree, preferably in electromagnetics, antennas, or related fields. A solid background in electromagnetics and antennas is required, with very good knowledge of metasurfaces and preferably machine learning. Experience with experimental work and applications of machine learning within electromagnetics is a plus. Proficiency in English is required. You may apply prior to obtaining your master's degree but cannot begin before having received it.

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Professors

Associate Professor at Technical University of Denmark

University Name
Country flag

Denmark

Research Interests

Machinelearning

In Vivo Sensing

Experimental

Tissue

Biomedical Engineering

Professor at Technical University of Denmark

University Name
Country flag

Denmark

Research Interests

Hardware Engineering

Computational Neuroscience

Photonic

Optical Communication

Optical Physics