Modeling and Control of Energy Consumption in Buildings: Thermal and Visual Comfort
In the context of global warming, a challenging issue is reducing the amount of energy consumption, specifically in the building sector and meanwhile respecting the existing constraints. This necessitates utilizing advanced modelling techniques and control strategies for buildings energy systems.
Design of a Multichannel Microfluidic AFM System
Design, Fabrication and Analysis of a Multichannel Hollow Cantilever Probe for the Fluid Force Microscope (FluidFM).
Development of a reflection-type near-field optical microscope
In this project a reflection-type near-field optical microscope will be designed, developed and characterized.
Automated nanoparticle loading
Levitation optomechanics systems consist of a nanoparticle that is optically trapped and levitated by a focused laser beam under vacuum conditions. The aim of this project is to design and build a reliable and automated nanoparticle loading process that can be triggered remotely.
Fast computation of Karma equilibria for interacting agents
This work builds upon very recent workon distributed interaction systems that we call Karma systems. We propose a mathematical formalism and numerical computation to predict user behavior in these systems. Your task is to 1. Improve existing code by making itfaster and more modular. 2.Design and run numerical experiments on individual agents interacting in a bigger social systemto understand the trade-offs of parameters that dictate what agents care about and how they interact.3. Quantify “social mobility”within the social system and find what parameters influence it most.
Theoryof Karma equilibria for interacting agents
This work builds upon very recent workon distributed interaction systems that we call Karma systems. We propose a mathematical formalism and numerical computation to predict user behavior in these systems.Your task is to 1. Extend the theory to the Markov chain case. 2. Evaluate the effect of having mixed populations of agents with different attributes. 3. Understandthe effect of time discounting on agent strategies and optimality of solutions. 4. Can we quantify social mobility in the social systemand connected it to population mixing?
Cardiac Magnetic Resonance Image Reconstruction Using Machine Learning
Dynamic Magnetic Resonance (MR) imaging offers exquisite views of cardiac anatomy and function. The objective of this project is to develop and implement methods that allow learning a data model from large sets of training data to be used in nonlinear data recovery from highly undersampled MR data.
Control of an autonomous paramodel
In this project an embedded controller will be designed and implemented on an adapted RC paramodel, allowing it to fly autonomously and safely in a wide range of conditions and loads.
Through Wall Sensing
By Through Wall Sensing (TWS), it is possible to sense through walls or similar structures. The goal of this project is to implement such a TWS system using Software Defined Radios (SDR) and the GNU Radio environment.
Combining Calcium Imaging and fMRI: Understanding the Neurophysiology of the Blood Oxygen Level Dependent Response
Advances in MR technology are rapidly increasing our imaging capabilities, however we still don't know what the BOLD signal actually represents. In the lab we try to gain a better understanding of the properties of brain circuits to increase the capabilities of fMRI.
Super paramagnetic manipulation of nanowires for engineered strain sensors used in biomedical implants
Fabrication of biocompatible strain sensors, resistive or capacitive to be used in-vivo to measure deformation of different tissues. The project is quite broad so many backgrounds will suit. Electrical Engineers, Material Scientist, Biomedical Engineers, among others.
Development of a multi-channel Transmit/ Receive Volume Coil (Antenna) for in vivo Magnetic Resonance Imaging with Zero Echo Time
Design and test a multi-channel transmit/ receive volume coil for in vivo zero echo time (ZTE) magnetic resonance (MR) imaging on a human scanner.
Automated identification of two-dimensional crystals based on optical contrast difference
The goal of this project is to develop an automated setup that is able to identify flakes of different thicknesses on Si/SiO2 substrates by analyzing the difference in optical contrast between the crystals and the substrate.
Optical trapping and cooling at telecom wavelengths
The goal of this master project is to set up an optical trap for a dielectric nanoparticle at telecom wavelengths and evaluate its performance for feedback cooling in comparison to existing experiments at 1064 nm.
Optimal State Estimation of a Levitated Nanoparticle
In this project, a Kalman filter will be implemented to estimate the time-varying state of a nanoparticle held in the focus of a laser beam. The state of the particle will then be used in a feedback loop to act back on the particle and to provide ultimate control over the nanoparticle's dynamics.
Optoelectronics with two-dimensional atomic crystals
For device applications, it is desirable to create functional hetero-structures by stacking two-dimensional atomic crystals on top of each other, forming so-called Van der Waals (VdW) heterostructures. We study the fabrication and properties of such optoelectronic devices based on 2D materials.
Self-induced back action trapping
Self-induced backaction (SIBA) trapping is a concept developed in optics for trapping of polarizable particles [1,2]. The goal of this project is the analyze, design and characterize an electromechanical analog of SIBA trapping.
DNA Aptamer-Based Electronic/Plasmonic Biosensors
Integrating DNA-based biorecognition elements termed aptamers that recognize chemical targets with high specificity and selectivity into next-generation electronic/plasmonic biosensors.
Convolutional neural networks for billiard state estimation
This project will use deep learning to recognise balls on a billiard table as part of the Automatic Control Lab's "DeepGreen" snooker robot project. We are building a robot able to take human-level accuracy shots, and this project will improve this accuracy further using reliable computer vision.
Multimaterial 3D Printing at the Microscale
3D printing is a family of emerging techniques for fabrication of functional devices. We are currently exploring methods to expand the range of printable materials, such as metals and polymers. Extending the range of materials will automatically lead to new opportunities for fabrication of functiona
3D Printing of a Microelectrode Array for Neural Applications
3D printing is a family of emerging techniques for fabrication of functional devices. Here, we make use of basics of electrochemistry and scanning probe methods to deliver metal ions locally and transform them into solid metal features. This is achieved by using glass capillaries with ultrasmall opening diameters with dimensions down to a few nanometers.
Design and test of novel Solid Polymeric Electrolytes (SPEs) for Lithium Ion Batteries
Current lithium ion batteries use liquid electrolytes that pose safety concerns in particular when used in electric vehicles. The goal of this project is to design, build and test novel solid electrolytes based on polymers.
Modelling of InP nanocrystal surfaces
In pursuit of new generation display technology, semiconductor nanocrystals are promising candidates for precisely tuneable emitters. Indium phosphide quantum dots (InP QDs) is currently the best available non-toxic blue-emitting nanomaterial. However, for commercial applications the performance sti
Machine learning of billiard ball dynamics
This modelling project supports the billiard-playing robot at the Automatic Control Lab. It considers the problem of reducing down complex billiard ball physics involving cue ball spin, using machine learning tools and camera feedback. To start in September 2019 or earlier.
Deep Learning Enabled Image Registration for Magnetic Resonance and Optoacoustic Tomography Data
This project aims to combine deep learning based image segmentation algorithm with an automated registration framework for optoacoustic and magnetic resonance images.
Design of an electrochemical pressure cell for battery
During lithium ion battery operation, volume changes in the battery’s electrodes lead to significant internal pressure. We characterize how this pressure changes battery structure and influences performance. For this purpose, we want to design an electrochemical pressure cell for battery testing.
Research assistant/intern: System integration for a robot billiard player
This flexible paid position is to perform integration work on a robot billiard player at the Automatic Control Lab. After half a dozen highly successful student projects the robot can take shots, and we now wish to integrate the overall system and make it as easy to use and reliable as possible.
Spin shots for a robotic billiard player
This project aims to take advanced shots using cueball spin with a robotic arm that has been developed to play billiards. It is an exciting opportunity to develop the vision-based localisation and shot-taking control needed to take such shots. To start in September 2019 or earlier.
Real-time Artificial Intelligence for a robot billiard player
This project is part of a new IfA project to develop a fully automated billiard playing robot, and is in particular concerned with its strategic AI. It will use a previous successful project as a baseline to implement a real-time AI for the robot. To start in September 2019 or earlier.
Implementation and application of a thermal conductivity setup for nanocrystal thin films
In this project a setup should be implemented to measure the thermal conductivity in thin-films. This includes sample microfabrication, understanding and improving the setup and extending it to nanocrystal films.
Biomedical Software Engineering - focusing on Continuous Integration, Distribution, and Linux Dependency Management
We develop Python-based Open Source pipelines which enable cutting-edge modelling and visualization of functional brain imaging data. As our pipelines grow in scope, we are looking to meet more stringent software engineering standards, and improve our distribution model with regard to accessibility.
Neuromorphic Processor Project
We are looking for PhD student interested in working at the leading edge of audio speech recognition using deep learning and incremental learning for personalization.
SCIDVS: Design and application of scientific dynamic vision sensor event camera
SCIDVS will develop a high performance scientific dynamic vision sensor (DVS) event camera, and apply it to challenging problems in space survey, aerodynamics, and neuroimaging.
Sensors Group, Inst. of Neuroinformatics semester/masters projects
The Sensors group ( ) at the Inst. of Neuroinformatics offers interesting projects spanning a broad range from circuit design to neuromorphic vision and audition with machine learning and artificial intelligence on robots
Modelling cardiac mechanics and function
The aim of the project is an in-silico replica of a patient’s heart starting from Magnetic Resonance (MR) imaging which will guide clinical evaluation of cardiac function, predict disease progression and augment MR data with low resolution and/or missing details.
Analysis, Modeling, and Simulation of an Isolated DC/DC LLC Resonant Converter for Server Power Supplies
This project focuses on the analysis of DC/DC LLC resonant converters for server power supplies that require wide input voltage range (300V-430V) and galvanic isolation. Soft switching and PCB winding transformer concepts are assessed and, in case of MA, a hardware prototype will be designed.
Realization of a Quasi 2-Level Flying Capacitor Converter Featuring New 1700 V SiC MOSFETs
A Quasi 2-Level Flying Capacitor Converter based halfbridge with 1700 V SiC MOSFETs will be realized in this thesis.
Nanoscale 3D printing of functional devices
3D printing is a family of emerging techniques for fabrication of functional devices. We are currently exploring methods for scaling down 3D printing technology onto nanoscale. This opens numerous exciting opportunities for fabrication of functional devices and materials for biomedical, sensing and energy applications.
Closed-Loop Use of a Digital Twin in Power Electronics
This work focuses on the realization of a DC/DC Buck converter, equipped with numerous sensors (e.g., voltage, current, temperature) that are necessary for implementing a Digital Twin / Industry 4.0 concept. The Digital Twin will be built based on the existing Optimization Platform of the PES Lab.
Software Implementation of a Rotor Position Measurement for a Servo Drive
Servo drives systems require information on the actual speed and rotor position to control the machine speed. Accordingly, servo drives are typically equipped with a position encoder. In this thesis, the data interface software between such an encoder and the drive control should be implemented.
Cellular infiltration detection in human heart transplant follow-up endomyocardial biopsy samples
Endomyocardial biopsy (EMB) is clinically used to detect heart transplant rejection. EMB histology leads to tissue alteration and use of a few 2D slices from 3D samples. Human EMB were imaged in 3D with synchrotron micro-tomography. Computational tools are needed for analysis and classification.
State estimation of phase shift transformers
Estimating the state of a power systems is an integral part of real-time power system analysis. In the state estimation process, measurements coming from power substations are compared to the power flow models of generators, lines and transformers to detect measurement or model errors. The method esti-mates the voltage magnitude and phase angle as well as active and reactive power flow in lines and transformers. The estimated values are then used in real-time network analysis to ensure a safe and efficient operation of the power system at all times.
Stroke Recognition using β-Variational Autoencoder
develop and implement a β-Variational Autoencoder to disentangle stroke lesions features
Mapping of biomolecule excretions next to cells using AFM integrated nanopores
Proteins, ions, and other excretions secreted from single cells are the key signaling factors to determine the interaction of cells with the extracellular matrix and the neighboring cells. We integrated a nanopore into an atomic force microscope (AFM) for sensing secreted molecules.
Multi-Echo Proton Spectroscopic Imaging to Map Cardiac Metabolite Levels
While MRI provides anatomical and functional information, magnetic resonance spectroscopy (MRS) allows to obtain biochemical information about substrate utilization and energy status of the heart. Multi-echo spectroscopic imaging can be used to map cardiac triglyceride and creatine levels.
Development of a MRI compatible DC-DC converter
Develop an MRI compatible DC-DC power converter. Electronics inside the MRI scanner are affected by the very strong background field, strong switching gradients and kW of RF power. The envisioned DC-DC converter should be immune to this harsh electromagnetic environment and shall not disturb the MRI
Master Thesis / 2nd Semester Project: Image-based Indoor Navigation
Many people rely on mobile navigation applications when they are visiting a new area. Such applications, however, fail to deliver the same service for indoor environments. This is mostly due to the attenuation of GPS signals inside buildings. We aim to replace GPS with image-based localization.
Transfer learning techniques for application of deep neural networks in 3D fluorescent microscopy images
Application of deep neural networks to 3D fluorescent microscopy datasets poses some specific challenges such as differences in their input distributions or scarce labeled data. We aim to address them by investigating transfer learning techniques such as domain adaptation of multi-task learning.
Machine Learning for Advanced Magnetic Resonance Perfusion Quantification
Magnetic Resonance (MR) perfusion imaging is a clinically established technique to detect coronary artery disease by visual assessment. However, quantitative evaluation of myocardial blood flow is desirable as it promotes objective diagnosis. Here, ML may help to avoid expensive fitting procedures.
Machine Learning in Stroke Imaging
The objective of this project is to develop and implement various machine learning methods to the recognition, segmentation, and diagnosis of brain strokes, using a large database of computer tomographic (CT) and magnetic resonance (MR) images.
Magnetic resonance thermometry for efficient CO2 capture reactors
Carbon capture and storage is anticipated to play a vital role in mitigating greenhouse gas emissions to the atmosphere. In this Master's project you will design a temperature-controlled model reactor that you will then image using a full-body human magnetic resonance imaging scanner.
Immobilization of Giant Lipid Vesicles for AFM-based Biophysical Membrane Measurements
- Establish an experimental system for force-controlled measurements in between phospholipid bilayer membranes. - Use microfabrication techniques to immobilize giant lipid vesicles on a surface. - Use a combination of atomic force microscopy and microfluidics to bring giant lipid vesicles in contact
Postprocessing techniques in acoustic resolution optoacoustic microscopy applied to human and murine skin
Acoustic resolution-optoacoustic microscopy (AR_OAM) images human and murine skin at good lateral resolutions and high depths. Applying appropriate postprocessing techniques to AR-OAM holds promise for improved skin imaging.

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