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Metabolomics is the study of small molecules in various tissues such as blood, urine, etc. Applications of metabolomics include monitoring of clinical trials and drug and biomarker discovery.
In a typical metabolomics experiment, samples are placed in numbered wells on plates and processed by mass spectrometer well by well, plate by plate. Analysis order is also called run order. One can interpret the resulting data as a high-dimensional time series, with the sample order as time and the relative intensity of individual metabolites per sample as values. Large metabolomic studies often involve the analysis of thousands of tissue samples that can take multiple days to weeks to process. In such large-scale studies, metabolomic measurements are prone to batch effects and instrumental drifts. Additionally, adjustments to the instrument by technicians introduce abrupt jumps, mostly occurring between plates. These drifts and jumps, which are only an artifact of the measurement, need to be removed in a pre-processing step.
Change (or break) point detection considers the localization of abrupt distributional changes in ordered observations. The classical scenario of changes in the mean of a univariate Gaussian variable has been thoroughly studied. Here, the data is i.i.d. Gaussian with constant mean and variance between breakpoints. We propose to relax this assumption and model the mean (corresponding to the drift) of the Gaussian random variables with splines.
- Biology, Information, Computing and Communication Sciences, Mathematical Sciences
- Master Thesis
| The Institute of Machine Tools and Manufacturing (IWF) and Advanced Manufacturing Lab (am|z) perform internationally leading research in the field of manufacturing engineering and machine tools. A recent research focus is put on additive manufacturing, sintering of alternative cutting materials, and machine learning. For a new industry related research project, we are looking for a talented student. - Engineering and Technology
- Bachelor Thesis, Master Thesis, Semester Project
| The Advanced Manufacturing Lab (am|z) performs internationally leading research in the field of manufacturing engineering. A recent research focus is put on sustainable manufacturing and thus enabling a circular manufacturing economy. One aspect is the recycling of manufacturing by-products/waste and its remanufacturing into new products. For a new industry related research project, we are looking for a talented student. - Engineering and Technology
- Semester Project
| Advancements in the field of Additive Manufacturing (AM) has created opportunities for disruptive innovation in the building construction industry. The Architecture and Building Systems group at ETH Zurich is using computational design, innovative materials and 3D printing techniques to create heat- and mass- transfer devices.
This thesis aims to measure the thermal performance of a 3D printed building façade capable of selective heat transfer, and predict the impact of the prototype on global building CO2 emissions.
| The global increase in temperature and humidity amplifies local impacts on livestock husbandry. Climatic extreme events like heat waves negatively affect milk producers, especially because cows experiencing heat stress may imply lower milk and milk component yields in Switzerland. This thesis uses rich data from swissherdbook and MeteoSwiss and provides causal estimates of temperature humidity shocks on milk production using an econometric analysis. Based on this assessment, the thesis quantifies its economic relevance, considering both quantity and price effects. Knowledge about climate change impacts on milk production provides highly relevant information for farmers and other stakeholders in the agricultural sector. - Agricultural, Veterinary and Environmental Sciences
- Master Thesis
| The Bosch IoT Lab (Prof. Dr. Oliver Gassmann, Prof. Dr. Felix Wortmann) – a joint initiative of the Institute of Technology Management at the University of St. Gallen, the Department of Management, Technology, and Economics at ETH Zurich, and the Bosch Group – is looking for:
Research Assistant and PhD Student in «Platform Business Models in Digital Healthcare»
Platform companies like Apple, Amazon, and Google dominate our economy. And indeed, successful platforms can be found in all industries, with healthcare being no exception. Many exciting healthcare platforms such as Babylon Health or PatientsLikeMe have already emerged. Moreover, incumbent players like Abbott or Dexcom have connected their smart MedTech products and embraced platform business models.
In light of these developments, we are looking for a personality with a strong will to create a meaningful impact. Are you eager to investigate how platforms will shape the future of health? Are you keen on developing business models and strategies in the realm of healthcare platforms and smart connected MedTech products? Are you excited about bringing your ideas to life? We are looking for you! - Business Information Systems (incl. Data Processing), Medical and Health Sciences
- PhD Placement
| The goal of this project is to build and characterize a linear displacement sensor. The student will learn how to work with optical systems, interferometers and state-of-the-art sensors. This project is in collaboration with iXblue company. - Electrical and Electronic Engineering, Optical Physics
- Master Thesis, Semester Project
| Complex physical processes are often modeled by large-scale dynamical systems that are difficult to simulate, predict and control. Model reduction is the art of approximating the behavior of such dynamical systems, while preserving their main features. A popular way to approach the model reduction problem is through methods based on moment matching (or rational interpolation), because of superior scalability and tractability properties as well as efficient data-driven implementations, such as Vector Fitting [1] and the Loewner framework [2]. The project hinges on recent advances in the area and explores new least-squares algorithms based on moment matching.
References: [1] B. Gustavsen and A. Semlyen, "Rational approximation of frequency domain responses by vector fitting", IEEE Trans. Power Delivery, vol. 14, no. 3, pp. 1052-1061, July 1999. [2] A. Mayo and A. Antoulas. A framework for the solution of the generalized realization problem.
Linear Algebra Appl., 425(2):634–662, 2007. Special Issue in honor of Paul Fuhrmann.
See also: https://en.wikipedia.org/wiki/Model_order_reduction - Systems Theory and Control, Systems Theory and Control
- Master Thesis, Semester Project
| Development of a closed-loop machine learning algorithm to extend the therapeutical uses of vagus nerve stimulation by improving the selectivity of electrical nerve stimulation, trained on a computational model and validated against experimental data. - Biomedical Engineering
- Master Thesis, Semester Project
| Wireless empowered micro/-nanorobotic systems enable novel and innovative medical therapeutics and diagnostics such as minimal-invasive surgery, targeted drug delivery, or enhanced imaging of diseased tissue. Immense research is conducted using various different external field-driven robot actuation methods, including magnetic, pneumatic, optical, and electric fields. Each technique brings its advantages and limitations that are matched for addressing one specific medical task. At the Acoustic Robotics and Systems Lab (ARSL), we focus on acoustically based robotic systems for life sciences and healthcare applications. Activation by ultrasound is attractive because ultrasound is safe to most biological systems, non-invasive, penetrates deep into the body of an animal model, and is widely spread in clinical institutions. - Biology, Engineering and Technology, Physics
- Collaboration, Master Thesis, Semester Project
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