 University of Zurich| Acronym | UZH | | Homepage | http://www.uzh.ch/ | | Country | Switzerland | | ZIP, City | | | Address | | | Phone | | | Type | Academy | | Current organization | University of Zurich | | Child organizations | | | Members | | | Memberships | |
Open OpportunitiesThis project will be carried out in collaboration with the FHNW Institute for Sensors and Electronics
Monitoring plant health is crucial for early detection of pests, identifying anomalies, and ensuring timely interventions. While numerous sensors are available for this purpose, selecting the most effective ones and eliminating redundancy remains a challenge. Additionally, transmitting large volumes of data to the cloud is power-intensive, especially in resource-constrained environments. To address these challenges, local preprocessing is essential to reduce data load and enhance efficiency. Leveraging neuromorphic hardware provides a promising approach to achieve low-power, real-time processing for plant status monitoring. - Engineering and Technology
- Bachelor Thesis, Master Thesis, Semester Project
| Neuromorphic computing represents a cutting-edge approach to designing computational systems by mimicking the architecture and functionality of biological neurons. One of the persistent challenges in fabricating neuromorphic devices is the cross-device response variability, which is often seen as a limitation. However, biological neurons and synapses are intrinsically heterogeneous, exhibiting a wide spectrum of responses that enhance robustness and adaptability. Inspired by this, recent computational study[1] demonstrated that neural networks composed of heterogeneous neurons—without the need for plasticity—significantly outperform their homogeneous counterparts, particularly in their reliability across a range of temporal tasks.
[1] Golmohammadi et al 2024, https://arxiv.org/abs/2412.05126
[2] Zendrikov et al, 2023 10.1088/2634-4386/ace64c
- Engineering and Technology
- Master Thesis, Semester Project
| Water management is critical to agriculture, especially with increasing climate change and water scarcity concerns. Traditional water supply systems often rely on fixed schedules or basic sensor feedback to control irrigation or water distribution, which can result in inefficiencies and wastage. With the rapid advancements in machine learning and neuromorphic computing, there is an opportunity to develop smarter, more adaptive water supply systems. Spiking Neural Networks (SNNs) on a hardware substrate[1], inspired by the brain's efficient way of processing information, offer a promising solution due to their event-based processing and low energy consumption.
This project proposes the development of a neuromorphic implementation of a Spiking Neural Network on DYNP-SE1[2] to optimize water supply using real-time moisture datasets [3]. The SNN will learn and adapt to environmental changes, ensuring that water is supplied only when necessary, reducing waste, and optimizing water usage. - Agricultural Engineering
- Bachelor Thesis, Master Thesis, Semester Project
| Glioblastoma, the most aggressive brain tumour in adults, interacts with the surrounding healthy brain to promote further cancer growth. However, it is challenging to study these interactions directly in the human brain. In response, we are developing a platform that allows us to study this phenomenon in more detail, with a particular focus on unravelling how cancer alters the electrical activity of brain cells. - Central Nervous System, Clinical Pharmacology and Therapeutics, Electrical Engineering, Oncology and Carcinogenesis
- Internship, Master Thesis, Semester Project
| In this project, you will work on the design and development of a micro-/nanomanipulator that is integrated into a cutting-edge single-molecule sensor. This system will enable precise positioning of the sensor chip and dynamic size control of the nanopore, critical for detecting protein modifications of varying sizes. This project offers an excellent opportunity for students interested in nanotechnology, hardware development, and biomolecular analysis to gain interdisciplinary experience and make meaningful contributions to advancing nanopore sensing technology. - Biomedical Engineering, Biosensor Technologies, Computer Hardware, Nanotechnology
- Bachelor Thesis, Master Thesis, Semester Project
| In this project, you will focus on the design and development of a custom hardware controller for piezoelectric actuators, enabling precise control of a micro-/nanomanipulator integrated into a cutting-edge nanopore sensor. The controller will provide high-resolution actuation voltages (up to 120 V) with closed-loop feedback for precise piezo actuation, critical for dynamic size control of interface nanopores. This project offers an exciting opportunity to combine hardware design, control systems, and nanotechnology in a real-world application. - Engineering and Technology
- Bachelor Thesis, Master Thesis, Semester Project
| Designing a test system and perform feasibility study of using spectral µ-filters on SPAD-array in TD NIROT system Pioneer, which is currently used in clinical validation study. The main potential benefit is faster and more precise signal acquisition, which results in overall speed boost of the system, shorter procedures for patients, and better data quality. - Optical Physics, Optometry
- Master Thesis
| This project aims to develop a neuromorphic system for object classification using tactile data, inspired by the human sense of touch. By integrating biomimetic sensors and a neuromorphic chip, the system processes spatiotemporal tactile information with high efficiency and low power consumption. The approach leverages spiking neural networks (SNNs) to encode and shapes in real time. The project focuses on designing algorithms optimized for the unique properties of neuromorphic hardware and evaluating performance in dynamic, real-world scenarios. This work has potential applications in robotics, prosthetics, and intelligent sensing systems, offering an energy-efficient solution for tactile perception tasks.
- Engineering and Technology, Medical and Health Sciences
- Bachelor Thesis, Master Thesis, Semester Project
| Real-time navigation of complex orthopedic surgeries faces challenges due to the dynamic surgical environment and limited visibility of patient anatomy. Intraoperative imaging modalities such as ultrasound and X-ray are commonly used to achieve some level of guidance, although often in a purely visual form[1, 2]. Ultrasound provides high-frequency, radiation-free imaging but is limited to localized areas and is prone to noise [3]. X-ray, on the other hand, offers a wider field of view with less noise but introduces radiation, restricting the number of images that can be safely captured during a typical surgery. Combining ultrasound and X-ray data could potentially balance these strengths, enhancing intraoperative anatomical reconstruction quality while reducing radiation exposure, something vital for achieving surgical navigation. However, to our knowledge, no existing setup or dataset currently integrates both modalities for this purpose.
This project focuses on developing a setup that enables sensor fusion of ultrasound and X-ray images to improve intraoperative surgical navigation. Alongside hardware setup, as is shown in Fig.1, a key objective is to establish a practical calibration method between an ultrasound probe and a C-arm X-ray machine. This will lay the foundation for creating a paired X-ray-Ultrasound dataset that can enable many downstream applications involving the said modalities. The final goal is to explore novel calibration techniques and system configurations that balance calibration accuracy with setup simplicity, facilitating efficient collection of joint ultrasound and X-ray datasets.
- Engineering and Technology, Information, Computing and Communication Sciences, Medical and Health Sciences
- Master Thesis
| Brain oxygenation, measured using Near-Infrared Spectroscopy (NIRS), is a critical health indicator, as inadequate oxygen can lead to severe and lasting brain damage. However, to ensure the accuracy of these measurements, it is essential to test and validate NIRS devices against a precise reference method, providing a reliable benchmark for comparison. These tests are conducted using a container filled with liquids that simulate the oxygenation process of blood, all within a controlled environment. - Biology, Engineering and Technology, Information, Computing and Communication Sciences, Medical and Health Sciences, Physics
- Bachelor Thesis, Course Project, Master Thesis, Semester Project
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