Eindhoven University of Technology
Eindhoven University of Technology (TU/e,
www.tue.nl), founded in 1956, is a world-leading
research university specializing in engineering science & technology. The Department of Electrical Engineering is responsible for research and education in Electrical Engineering. The TU/e is the world's best-performing research university in terms of research cooperation with industry (#1 since 2009). Eindhoven is also the world's most innovative city with the highest number of patents per resident.
Electronic Systems group at the TU/e
The Electronic Systems (ES) group (
www.es.ele.tue.nl) comprises three full professors, two part-time full professors, two associate professors, six assistant professors, about 40 PhD candidates and postdocs, and several technical and support staff. The group has excellent infrastructure that includes individual computers, servers, state-of-the-art FPGA and GPU farms, sensor- and ad-hoc networking equipment, and a comprehensive range of electronic-design software. The group is member of Europractice and CMP, having access to advanced CMOS technologies down to 28nm. The group is authorized user of ARM DesignStart design suite, and has acquired the ARM Cortex M0 and M4 processor IP from ARM.
The ES group is world-renowned for its design automation and embedded systems research. It is our ambition to provide a scientific basis for design trajectories of digital electronic circuits, embedded and cyber-physical systems. The ES group excels in the area of digital VLSI circuit and system design. A variety of state-of-the-art chips have been developed by our ES group together with our industrial partners, such as NXP Semiconductors and imec - Holst Centre.
PhD /Post-Doc position in the BrainWave project (
brain-wave.nl/)
Brain-related diseases, such as epilepsy and Parkinson's Disease (PD), are severely degrading
people's quality of life. Few of the disease cases can be cured by medication alone. Many patients have to go to specialized hospitals to receive continuous monitoring of their electroencephalogram (EEG) signals, which is costly and impacts patient's well-being. Current EEG sensing and processing platforms used in advanced hospitals are bulky and wired to the patient's head. The used equipment is also power hungry and not self-sustainable, thereby far from being wearable, prohibiting continuous (24/7) monitoring. A solution is urgently needed to help these patients and raise their quality of life.
In this BrainWave project, we research and develop a wearable brainwave processing platform enabling 24/7 healthcare of epilepsy and Parkinson's disease patients in non-hospital environments. Its key contribution is a novel brainwave processor which will analyze and interpret the EEG signals that are collected non-invasively by a multi-channel sensor interface. Ultra-lowpower, on-chip context-aware and patient-specific signal processing together with features such as data logging and cloud connection will make this brainwave processing platform really wearable and suitable for non-hospital environments.
In this project, the Electronic Systems (ES) group at TU/e collaborates with the Signal Processing System (SPS) group at TU/e, Kempenhaeghe, and the Donders Institute at the Radboud University Nijmegen. Two of our industrial partners NXP and TMSi will be heavily involved in the chip and system development as well.
Three PhD students are involved in this project. The first PhD student is in charge of signal processing algorithm development, and is supervised by professors from the TU/e SPS group, Kempenhaeghe, and Donders Institute. A second PhD student is concerned with new ultra-low-power circuit-level implementation methods and the process technology interface, supervised by professors from the TU/e ES group.
In this third position the focus will be on ultra-low-power architectural innovations for mapping the new brainwave processing algorithms. The selection and modification of algorithms, and their ultra low-energy (combined HW-SW) implementation, without compromising functional performance, is a key challenge in this assignment.
Since two other PhD positions are already active for some time, we are looking either for a PhD candidate with already substantial experience in architecture creation for signal processing algorithms to have a flying start. Another option is to apply as Post-doc.
The PhD involved with signal processing is being supervised by Prof. Dr. Richard van Wezel, Prof. dr. Johan Arends, and Dr. Mike Cohen.
The PhD involved with ultra-low-power circuit design is supervised by Prof. Dr. José Pineda de Gyvez, Prof. dr. Henk Corporaal, and Ir. Jos Huisken. You will be supervised by these people as well.