Doctoral School for Dependable Electronic-Based Systems.
Electronic-based systems (EBS) make our world “smart” by combining advanced electronics and software, often in networked systems that interact with the physical world through sensors and actuators. Most EBS applications in production or transportation are safety-critical: EBS failures may cost human lives. We thus aim to find fundamental concepts and methods, but also application-oriented tools to make EBS dependable, where dependability summarizes attributes of a system allowing humans to trust EBS.
The PhD project.
This project investigates 1-bit (two-level) signals and systems to provide uniform representations, signal processing blocks, and algorithms for 1-bit mixed-signal processing. Driven by the trend to bring ever faster computing units onto the market, transistor sizes have been scaled and their properties optimized for highest possible switching speeds. Thus, 1-bit signals are ideal for processing in digital circuits, but they are also used to generate analog signals for highly-efficient power conversion and power amplification as well as for high-speed sensing. It naturally leads to the questions if we can find unified representations for 1-bit signals (either in continuous- time or discrete-time), if we can build reliable systems to sense and generate 1-bit signals, and if we can devise algorithms for 1-bit signals and systems.
In particular, we will further investigate compressive sensing and machine learning approaches to 1-bit sampled signals, jointly addressing analog and digital signal processing of 1-bit signals to develop algorithms and systems that outperform state-of-the art converter concepts.
Master’s degree in electrical engineering, applied mathematics, communications, computer engineering
Very good skills in signal processing, mathematics, electronics
Basic knowledge in sampling theory, machine learning, is an advantage
Experience with at least one programming language (e.g., Python, Matlab, C) is required
Our research group.
The research focuses on mixed-signal processing where methods from time-varying and nonlinear signal processing, sampling theory, machine learning and optimization are used. We are particularly interested in the interplay between analog and digital circuitry, algorithms and physics to design and improve next generation algorithms and devices.
This position is funded for 4 years and is paid with a minimum gross salary of 38,588.20 €/year for a full-time employment (40 h/week).