Offered thesis

The high-frequency power amplifier (RF PA) plays a central role in every transmission and reception chain. Such amplifiers are not only used in classic applications such as mobile communications, aerospace and defence, but also in medical technology – especially in magnetic resonance imaging (MRI).

In MRI systems, a powerful RF pulse is emitted at the so-called Larmor frequency – i.e. the frequency at which the hydrogen nuclei (protons) precess in the static magnetic field. In a 3-Tesla MRI system, this frequency is approximately 128 MHz. The RF pulse excites the spins of the protons. When they return to their ground state, the protons emit energy in the form of RF signals, which are measured and used for image reconstruction.

In order to integrate AI algorithms, e.g. in the form of neural networks, into wireless communications systems, it is necessary to drastically reduce their resource consumption with regard to an embedded implementation. This begins with the selection of a suitable model architecture and often involves well-known optimization methods such as quantization and pruning.

We will build an end-to-end RFIC design flow (schematic → layout → EM → co-simulation) both with open-source tools and in commercial environments, and correlate the results.The work includes IC design (schematic, layout, verification) in Cadence/ADS and Ansys HFSS/CST, as well as with open-source tools (Qucs-S/Ngspice/Xyce, KLayout/gdsfactory, openEMS, scikit-rf).

The goal is to develop an algorithm or machine-learning approach that automates parts of RFIC design using open-source design tools. We focus on passive components such as transformers, baluns, and antennas. Based on desired performance parameters (e.g., target frequency, bandwidth, insertion loss, impedances, efficiency), a tool should generate the optimal geometry.

The high-frequency power amplifier (RF PA) plays a central role in every transmission and reception chain. Such amplifiers are not only used in classic applications such as mobile communications, aerospace and defence, but also in medical technology – especially in magnetic resonance imaging (MRI).

In MRI systems, a powerful RF pulse is emitted at the so-called Larmor frequency – i.e. the frequency at which the hydrogen nuclei (protons) precess in the static magnetic field. In a 3-Tesla MRI system, this frequency is approximately 128 MHz. The RF pulse excites the spins of the protons. When they return to their ground state, the protons emit energy in the form of RF signals, which are measured and used for image reconstruction.

Superparamagnetic iron-oxide nanoparticles (SPIONs), composed of a magnetic iron-oxide core and a tunable non-magnetic coating, exhibit rapid magnetic response along with exceptional stability and biocompatibility [1], [2]. These characteristics have fostered their applications in diverse medical fields including drug delivery [3], diagnostic imaging [4], and hyperthermia therapy [5]. The characteristics of nanoparticles are closely related to their structure. Their structure is well layered. Crystals, iron oxide nuclei, aggregates, clusters and agglomeration are gradually formed as the scale increases. The formation of these different hierarchical structures determines the macroscopic properties of the final nanoparticle.

Einleitung Die Messwerte von Photodioden, die sichtbares Licht oder ein breiteres Spektrum erfassen, hängen stark vom Einfallswinkel des Lichts ab. Daher verfügen die meisten hochgenauen Referenzinstrumente über einen Diffusor, um eine gleichmäßigere Lichtverteilung zu gewährleisten. In vielen Anwe...

We are looking for a motivated master’s student for an exciting research internship in the field of developing a multispectral light sensor array. Background Accurately measuring light parameters such as lux, photosynthetically active radiation (PAR), irradiance, UV, and IR can be expensiv...

Description We are looking for a motivated intern (m/f/d) to develop an interactive XR app using Xcode/Swift. The application will provide a step-by-step assembly guide for a brick-based robot, where components and assembly steps are visualized in an XR environment. Additionally, a Bluetooth contro...

Master’s Thesis / Bachelor’s Thesis / Research Internship Description The use of synthetic datasets in computer vision is becoming increasingly important, especially for training neural networks. This project aims to create a digital 3D model of a parking deck in Blender to realistically simulate ...

We will build an end-to-end RFIC design flow (schematic → layout → EM → co-simulation) both with open-source tools and in commercial environments, and correlate the results.The work includes IC design (schematic, layout, verification) in Cadence/ADS and Ansys HFSS/CST, as well as with open-source tools (Qucs-S/Ngspice/Xyce, KLayout/gdsfactory, openEMS, scikit-rf).

The goal is to develop an algorithm or machine-learning approach that automates parts of RFIC design using open-source design tools. We focus on passive components such as transformers, baluns, and antennas. Based on desired performance parameters (e.g., target frequency, bandwidth, insertion loss, impedances, efficiency), a tool should generate the optimal geometry.

Student Assistant (m/f/d) Intelligent Parking Space Detection Using a Multi-Camera System and CNNs

Description The efficient detection of parking occupancy is a key component of smart traffic management systems. This project aims to utilize a multi-camera system to monitor a parking deck in Erl...