Development of a robotic endotracheal intubation system
The scope of this project is the development of a prototype to perform robot-assisted endotracheal intubation.
Functional model design of a novel bedside measurement system
Development of "proof-of-concept" of a bedside measurement system for patients with cerebral hemorrhage.
Computational modelling of human fear memory
The goal of the project is to improve computational/biophysical models of autonomic nervous system readouts of human fear memory.
Predicting search trajectories in a computer game
The goal of this project is to understand human cognition in a computer game and predict behaviour of individual humans.
Master Student Position (MSc or MD) in Translational Diabetes
We are seeking for a talented master student to support our research in translational diabetes. Our research focuses on the role of the immune system in metabolic disease, especially the contribution of intestinal innate immune cells in obesity and diabetes.
Electrical resistance tomography with conductive foam
Purpose of this project is to validate use of the conductive foam as a touch/pressure sensing interface with the use of electrical resistance tomography techniques. Electrical resistance tomography consists of imaging the conductivity distribution inside an object by injecting current and measuring potential distribution across the surface of the object.Main task in the project is to build the electronics hardware for the electrical resistance tomography experiments. Interested students will also get to work in the simulation and computation aspect of the problem
Single-neuron Electrical Stimulation
Master thesis on precise single-neuron electrical stimulation. The work will cover both engineering aspects, as the electrical stimulation and the data analysis, and biological applications, as cell culturing and immunostaining.
Fabrication and optimization of functional lattice elements for ultra-lightweight active structures
Integrated sensors and actuators in sandwich panels serve dual functions of adaptation as well as reinforcement, thereby leading to ultra-lightweight active structures. Additive manufacturing serves as the best tool in fabricating functional, at the same time load-bearing sandwich panels given the c
Define effective DMD parameters on design for laser 3D printing of metallic parts
The Direct Metal Deposition (DMD) or laser cladding is recently further developed to be applied not only in the repairing applications but also manufactures 3D complex metallic part.However, feasibility analysis should be done prior shape optimization step to be aware of fabrication capabilities and
Improving 3D-Printed Mold Resolution for Fabricating Capillary-Driven Microfluidic Networks
The student will devise and optimize a master mold printing protocol for increasing the resolution of 3D printed microstructures by casting-shrinkage cycles of a polyurethane polymer. Once established, the protocol will serve in designing, producing and testing novel open microfluidic networks.
Developing quantitative MRI methods in SCI: Towards a tool for detecting tissue plasticity of brain and spinal cord
In this project, we aim to develop an advanced multi-modal qMRI pipeline to improve the sensitivity to specific microstructural tissue features simultaneously in brain and cervical cord.
Electrophysiological analysis of stretch activated ion channels under microgravity conditions.
Overexpression of specific stretch activated ion channels in Xenopus laevis oocytes, by DNA microinjection. Subsequent characterization of the channels by electrophysiological methods under normal gravity and microgravity
Edge mode velocities from tunneling spectroscopy
We have developed a new technique in our group to study the integer quantum Hall edge states in GaAs. In contrast to previous works, this new method allows us to determine the velocity of edge modes simultaneously along with the whole lifecycle of the edge states from formation to depopulation.
Master Thesis: Computational modeling and simulation of flow and transport in the Kidney
The kidneys are responsible for filtration of blood and removal of waste products of metabolism. To date, kidney O2 regulation is poorly understood. With the help of computational methods and using the latest supercomputers, we aim to determine oxygen distribution in the kidney.
Active Perception for Unknown Object Classification
The main objective of this project is to develop an information-based active perception algorithm for the autonomous reconstruction and classification of unknown 3-D objects.
Endress Postdoctoral Fellows in Quantum Science and Quantum Computing
The Center for Quantum Science and Quantum Computing (QSC) of the Universities of Basel (Switzerland) and Freiburg (Germany), embedded in EUCOR – The European Campus, invites applications for up to ten Georg H. Endress Postdoc Fellowships to start in 2018.
PhD position in 3D electrospun hydrogel cell scaffold with opto-responsive fiber core for extracellular oxygen and pH mapping
Fully funded PhD studentship available on 3D optically responsive nanostructured cell scaffolds. This is a 4-year PhD (unlike the standard 3.5 year UK PhD), as it is within the EPSRC Centre for Doctoral Training in Intelligent Sensing and Measurement. You will learn how to synthesize and characterize optical nanostructures for monitoring clinically relevant bio-markers, how to fabricate 3D nanostructures (3D nanoprinting), how to integrate optical probes within cell scaffolds, how to assess in vitro sensor performance and how to work with cell cultures. Within the project you will use state-of-the-art characterization techniques. Part of the work will be carried out at the material research institute Empa in St. Gallen (Switzerland) (ETH domain).
Lagrangian Numerical Scheme for Advective/Diffusive Transport
For the simulation of transport in fluid flows, Lagrangian numerical schemes have the advantage that they do not suffer from numerical diffusion. In this project, a new Lagrangian scheme shall be developed that is representing the advective/diffusive motion with a stochastic process.
Internship Switzerland / China
Brütsch-Ruegger, the leading supplier of tools for industry, offers an intership with a training period at the head quarter in Urdorf (Switzerland) and a field analysis preparing the implementation of an IoT-Solution in Shanghai (China).
Congruency of different devices to detect motor imagery activity: a validation and test-retest reliability study
Motor imagery is a powerful technique that originated in sports psychology and is used in rehabilitation, in particular in neurorehabilitation. Objective measurements of motor imagery-related brain activity is important but expensive, time-consuming, and limited to stationary recordings, e.g. fMRI.
The emergence of subjective feelings during foraging under predation threat
Non-human approach-avoidance conflict tests are classic paradigms to elicit anxiety-like behaviours, and mimick aspects of foraging for food while under threat of predation. We have recently translated this class of paradigms to humans (e. g. Bach et al. 2014, Current Biology; Korn et al. 2017, Biological Psychiatry). However, it is unclear how behaviour in this paradigm relates to subjective feeling.
The Walking Canvas - Actuation and Control Design for a Robotic Art Installation
This project is a collaboration between the RSL, the Wyss Zurich, and the artist duo Pors&Rao that creates art using robotics. The goal is to design an actuation and control concept for the Walking Canvas, which should, ultimately, freely walk through an exhibition space.
Graphene Membranes for Ultrafast Separations
Ultrathin nanoporous graphene or graphene oxide membranes enable ultrafast permeation, while providing molecular selectivity. This project focuses on fabrication techniques, particularly for scaling up.
Particle Simulation of Electric Discharge Machining (EDM)
In essence, the created electric spark between the electrode and the workpiece in EDM generates an intense heat with temperatures reaching the range of 8000 to 12000 degrees Celsius. This temperature, strictly speaking, is enough to melt the materials of any kind. While the empirical investigation o
Particle Simulation of Laser Manufacturing Processes
The numerical study of laser manufacturing processes is of paramount importance from both an ecological and an economical perspective. More specifically, the application of meshfree (particle) methods in laser manufacturing processes has seen an exponentially growing share of interest since its debu
Novel fluid designs enabled by additive manufacturing
Additive manufacturing makes it possible to fabricate novel designs for fluid systems. Examples are mixers, nozzles, and burners. Goal of this work is to design, manufacture, and test a AM-made fluid flow application. To accelerate the geometry creation, tools of design automation shall be applied.
Bone marrow models for heightened recruitment of Hematopoietic Stem Cells
For bone marrow transplants, large numbers of hematopoietic stem cells (HSCs) are needed. However, the in vitro expansion of HSCs remains a major challenge. So, an attractive solution is the development of 3D scaffolds that can recreate the bone marrow niche, where HSCs can be cultured and expanded.
Integrated Photonics and Plasmonics – Plasmonics Modulators
In this work we investigate new plasmonic modulator approaches and their viability on different material platforms.
3D Printing Silicones
Optimisation of Printing process
Radiation Pressure Sensor
The objective of this project is to develop a sensor for measuring the radiation pressure of light. A high-reflectivity dielectric mirror will be be mounted on a nanoscale cantilever with very low stiffness. An incident laser beam will be reflected and measured by a weak probe laser.
Electronic processing of quantum random numbers from a photonic chip
The goal of this project is to develop a complete interface, control and processing electronic system based on state-of-the-art FPGA technologies to integrate the optics with current IT systems.
Optical sensing with a resonant tunneling device
In this project, an optical multilayer structure will be analyzed, fabricated and characterized. The objective is to fabricate the device and measure the reflectance spectrum for different angles.
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 forces in structured fields
The goal of this project is to develop a calculational toolbox allowing investigation of optical forces generated by structured fields when interacting with nano-optical building blocks.
Influence of moisture on the SLM process
The SLM process is strongly influenced by the raw material - the powder. Metal powder can absorb moisture during the SLM process chain. Moisture degrades the component properties or even prohibits the processing of powder. This negative influence is to be investigated in this thesis.
Influence of particle size distribution on the SLM process
Research has shown an influence of the particle size distribution on the process parameters (such as laser power and scanning speed) of the SLM process. This influence is to be investigated in this thesis.
2D Polymer Membranes
With atomic-scale thickness and inherent pores at 1-nm, two dimensional polymers are morphologically the ideal membrane material. We aim to develop methods to manufacture such membranes.
Redesign of a miniature fluorescent microscope
To study biological neuronal networks, we use miniaturized microscopes that allow us to record large-scale neuronal network activity in freely behaving mice. We are looking for a student who can help us push the imaging and data transmission capabilities of our current miniaturized microscope.
High Throughput Pattern Matching of fMRI Maps and Molecular Features
We develop high-level fMRI pipelines with the goal of increasing automation and throughput in the field of animal imaging. For this project we are looking to leverage information theoretical metrics and large scale databases in order to better relate fMRI data to underlying molecular features.
Vectorising historical transport maps
IVT is looking for a HiWi to support us in vectorising historical transport maps. The research project aims in the reconstruction of Western Europe’s historical transport network.
Window-less ceramic volumetric solar air receiver: assembly and testing
The objective of this work is to modify an existing volumetric solar receiver and test it on the high-flux solar simulator at ETH. Experimental work, suitable for a Master thesis in mechanical/ thermal/energy engineering. Background in heat transfer and lab work preferred.
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.
Analysis of Numerical Methods for Boundary Treatment in Wall-Bounded Turbulent Flow Simulations
In this project, a recently developed immersed boundary method for accurate Large-Eddy Simulations of compressible wall-bounded flows will be validated and applied to (simplified) internal combustion engine flows.
Master thesis "Gestagen metabolites during late pregnancy in Asian elephants (Elephas maximus)"
Elephants are among the few mammalians which do not use progesterone as functional gestagen. A detailed analysis of specific progestins using LC-MS/MS will unravel the gestagen meabolites of Asian elephants during late pregnancy and calving.
Student Research Assistant
The ADRL is looking for a mechanical engineering student research assistant (Hilfs-Assistant) with a talent and practical experience for workshop work, CAD software and basic mechanical design.
Potentialanalyse zum Einsatz von ΔΣ-Modulatoren für die Positionsund Winkelsensorik
Die Baumer Group zählt zu den international führenden Herstellern von Sensoren und Messinstrumenten. Das Produktsegment Motion Control ist auf die Erforschung, Entwicklung und Herstellung von industriellen Sensoren zur Messung von Winkeln und Drehzahlen spezialisiert. Das Produktspektrum reicht dabei von klassischen Drehgebern für die Fabrikautomation, lagerlosen Drehgeberkits speziell für die Windenergieerzeugung hin zu Heavy Duty Drehgebern für den Einsatz unter widrigsten Bedingungen. Baumer setzt dabei insbesondere auf optische und magnetische Sensorprinzipien.
Line Clustering and Description for Place Recognition
The goal of this project is to develop a place recognition pipeline using RGB-D or stereo cameras, by extracting line clusters.
Learning the Weights of a Trajectory Optimizer to Generate Aesthetically Pleasing Quadrotor Camera Motion
The goal of this project is to develop a machine learning pipeline which learns weight parameters for an existing quadrotor camera optimization scheme given characteristics of a camera path (e.g., number of keyframes, etc.).
Implementing a Predictive Text Entry Method for Swiss German
The goal of this project is to develop a predictive text entry method which supports writing Swiss German based on an exist-ing data set of Swiss German WhatsApp messages.
Deep Learning for Sensor-Enhanced Eye-Tracking Glasses
This project applies eye tracking to the study of the root causes of short-sightedness. This is based on our own sensor-embedded eyeglasses which collect information on ambient illumination, eye responses, and working distance. Data from a pilot study with 15 adults will be analyzed using ML.
Master's Thesis: Develop an Online SLAM System for maplab
The online front-end of maplab is currently limited to localize only within a pre-built (and constant) localization map created in an earlier session. However, many robotics applications would benefit from localization against previous sections of the session that is currently being built. This is
Master Thesis about Nonlinear Photonics of Nanostructures
We propose to work on the realization and the advanced optical characterization of a new class of nonlinear optical materials based on the assembly of perovskite nano-particles (nano-oxides) in disordered, correlated and hierarchical structures.
PhD Student in Nonlinear Photonics of Metal-Oxides Metastructures
The PhD student will investigate a new class of nonlinear optical materials and their applications as compact photonic devices. The interest targets the increasing demand for miniature optoelectronic devices that are efficient, robust and easy to fabricate for large scale applications.
Numerical Representation of 3D Cutting Geometries
This work is aimed at developing a robust computational tool for implicit geometry representations of cutting processes in 3D. The primary focus within this project will be on a popular technique, called the Particle Level Set method.
Selective Laser Melting Processing of Shape Memory Alloys
Shape Memory Alloys sind für viele Industriezweige, v.a. die Medizinal-Technik, sehr interessante Materialien. Ihre Verarbeitung mittels additiver Fertigung ist aktuell aber noch nicht standardmässig etabliert, weshalb in dieser Arbeit ein Schritt in diese Richtung gemacht werden soll.
Desired Porosity in Selective Laser Melted Parts
Selective Laser Melting (SLM) enables the tuning of material properties while the material is built up. An interesting opportunity of SLM is the manufacturing of porous structures, since these offer a wide range of new applications. Thus it is worth analysing the structures in detail.
Electrospun, double-layered scaffolds for 3D Skin Tissue Engineered
This project is part of the Zurich Hochschulmedizin Flagship Project “Skintegrity”, with a collaboration between ETHZ and USZ. The student, who ideally has experience in electrospinning and cell culture, will participate in the development of double-layered nanonfibrous scaffolds for 3D skin tissue engineering.
Soft robot snakes
We would like to investigate methods for building soft robots, ideally using reasonably priced materials and fabrication techniques, such as PU-foam moulding and/or 3D printing. As a proof-of-concept, we envision a robotic snake fabricated as a single flexible body with internal wiring.
Chalmers, Sweden: PhD student position in Human-Computer Interaction (HCI) & Visualisation
Information about the project: The European Marie-Sklodowska-Curie Innovative Training Network TOMOCON joins 12 international academic institutions and 15 industry partners. URL:
Sleep neurobiology: Acoustic Stimulation on Motor Learning
Slow oscillations (SOs), the hallmark of Slow-Wave Sleep (SWS), play a major role in neural plasticity and sleep-dependent memory formation, including learned motor tasks. We are studying the effect of acoustic modulation in SWS on motor learning in rats.
Develop an Additive Manufacturing Based Thermal Management Module for the ALPA PLATON Platform
A new cooling module has to be developed and added to the camera system to enable uninterrupted operation and avoid costly interruptions on the set due to overheating. Polymeric (SLS, FDM) and and Metal (SLM) additive technologies are accessible for the manufacturing of the module.
Technology based assessment of upper limb function during the rehabilitation of neurological patients
The Virtual Peg Insertion Test (VPIT) is a novel tool to measure upper limb function. It can provide quantitative information during the rehabilitation of neurological patients that can help to better understand the motor recovery process or the effect of therapeutic interventions.
Simulation methods
In this project, we wish to compare various simulation methods found in today’s physics-based animation, as well as engineering communities, and understand how they perform when simulating non-linear elastic materials at various resolutions.
Brain measurement with functional near-infrared spectroscopy (fNIRS)
In this internship, you perform brain measurements with a novel functional near-infrared spectroscopy device.
Multi-modal cross-sensor learning
Self-driving cars are typically equipped with dozens of heterogenous sensors, including regular cameras, LIDARs, sonars, IMUs, etc. Many perception pipelines are supported by machine learning methods, but these typically consider one sensor in isolation, and there is little research done towards the possibilities which are allowed by having data from heterogeneous sensors. For example: • Can we detect anomalies or faults in sensor readings by comparing them to sensor readings of another type of sensor? • Can we use already trained machine learning algorithms on one sensor to jump start training on another sensor, for tasks such as object detection, localization, and control? In this thesis, you will explore these possibilities working primarily on an autonomous go-kart.
Computational Fluid Dynamics (CFD) Simulation for Evaluation of Aortic Blood Flow, Machine Learning
Set up of a CFD simulation of a human aortic arch in order to evaluate current patterns using machine learning.
Robustness of end-to-end learning for autonomous vehicles control
Recently, several papers have shown that it is possible to learn an “end-to-end” policy that directly maps images to control inputs using neural networks. We have observed this to work well for imitation learning for simple reactive tasks. For example, one of the AMOD projects showed that it is possible to replace the lane localization and control pipeline of a Duckiebot using a single CNN. However, there are several open questions; basically, nobody knows why it works and, most importantly, when exactly it would not work. Therefore, these techniques cannot be deployed on safety-critical systems such as self-driving cars.
Task-driven perception for autonomous vehicles
Currently, robotics perception pipelines are very inefficient, because the problem is formulated as “estimating the state”, with no regard to what part of the state is relevant for planning and control. For example, for a self-driving car, it is very important to sense what is in front of it, when going forward, and less important to know what happens behind, because that part of the world will have a negligible impact on the decisions to make. On the other hand, when doing parking maneuvers, it is important to check what is behind the car. Currently these “attention mechanisms” can be coded using ad-hoc heuristics, are very fragile to tune, and are considered very risky, because if there is a mistake, a missed detection of an obstacle might have fatal consequences.
Minimum-violation planning in uncertain environments
Minimum violation planning is a commonly used method for path planning in self-driving cars, because it allows to mix continuous objectives (finding the shortest path) with discrete constraints that come from logic, such as the constraints arising from the rules of the road. However, it is unclear how to adapt minimum violation planning to uncertain environments, where the uncertainty comes from either sensor noise, ignorance about models, or ignorance of other actors’ intentions.
Scalable control architectures for autonomous vehicles
Robots come in all shapes and sizes. And for each one, currently the software is created ad hoc. The software created for a robot cannot automatically be made to run on another different robot, even if the sensors, the dynamics, and the task are similar, because it depends on a set of implicit assumptions about the resources available, the precision of the sensors, the noise in the process, and so on. Is it possible to create a scalable architecture that works on a wide range of platforms? For example, can we create an autopilot that can drive the humble $150 Duckiebot, a professional $10,000 racing go-cart, and a full-sized self-driving car, and achieve in each case the maximum performance given the resources constraints?
Education on demand
Education is ripe for disruption. We believe that there are many opportunities for improvement, based on the ideas of customization and continuous measurement and feedback. In particular, we would like to address the needs of the so-called “independent learners”. The internet allows flocks of enthusiastic independent learners, who are not enrolled in traditional institutions, to have access to plentiful education material. However, they lack the mentorship, and so their learning experience is ineffective. This thesis will create the world’s first “education on demand” service.
Hardware design for a worldwide robotics education experience
One of the goals of the Duckietown project is to design a low-cost robotic platform for education. Suppose there are 1 million people in the world interested in learning robotics using Duckietown. How to make it feasible for 1 million people to have their Duckiebot and Duckietowns? In this thesis, you will optimize the design of the platform to make it feasible for everybody in the world to take part in the Duckietown experience.
Task-driven closed-loop auto-tuning of Dynamic Vision Sensors
The biologically-inspired Dynamic Vision Sensor (DVS) developed at ETH offer desirable traits such as microsecond latency and asynchronous sampling, in addition to high dynamic range, which address the known limitations of traditional image sensors. This is made possible by a pixel design that, instead of outputting a luminance value (as a CCD sensor), it perceives variations in luminance, providing signed flags and timestamps (events) only when this variation hits user-defined thresholds. Biases can be controlled at high frequency. In this thesis, you will implement closed-loop control strategies to optimize the biases as a function of the current environment and task, with the goal of generating the most informative measurements for any situation.
Master thesis in the field of additive manufacturing, product design, computational fluid dynamics and testing
This master thesis deals with a specific problem from the Sulzer product development portfolio, e.g. mixing nozzles for biological and technical applications.
Event-based control of autonomous vehicles
Biological vision systems are driven by events happening within the scene in view, e.g., motion. Biologically inspired event-based sensors, such as the Dynamic Vision Sensor (DVS), sample the scene at a rate that is determined by the observed phenomena and at a rate that is potentially orders of magnitude higher than typical image sensors. Moreover, in an event-based sensor each pixel samples the scene asynchronously, i.e., independently from the others, drastically reducing the data rate hence removing the bottleneck from the feedback control pipeline. While this novel sensing paradigm promises breakthroughs in control related applications, especially for “fast" systems such as autonomous vehicles, it is yet unclear how to best exploit this event-based data at an algorithmic level.
Internship at Sulzer Applicator Systems
Sulzer’s core is flow control and applicators. The company specializes in pumping solutions, services for rotating equipment, and separation, mixing and application technology. Innovation and research and development play a pivotal role in the sustained success of Sulzer. Our innovative solutions add value and strengthen the competitive position of our customers.
Fluid Dynamic Characterization and Analysis of Optimization Potential for an Extra-corporeal Rotary Blood Pump
Extra-corporeal rotary blood pumps are used as a short-term ventricular assist device (VAD), often as a right ventricular assist device (RVAD) after left VAD (LVAD) implantation, or in combination with an oxygenator during extra-corporeal mebrane oxygenation (ECMO). Such a pump consists of a rotatin
M.Sc. Thesis: Large Scale 3D Semantic Reconstruction
Joint volumetric 3D reconstruction and semantic labeling has pushed the state of the art as concurrent estimation leads to better estimates of both entities. By using adaptive data structures in combination with deep learning we want to make recent approaches more scalable and accurate.
PhD student for Resistance Gene Identification in the Xanthomonas - Ryegrass Pathosystem
Project associated to the international COST Action «CA16107 EuroXanth »
M.Sc. Thesis: Learned Semantic Multi-view Refinement
Joint volumetric 3D reconstruction and semantic labeling has pushed the state of the art as concurrent estimation leads to better estimates of both entities.
Epidermal patterning in wheat
In this project, we would like to extend our knowledge to: Identification of environmental factors controlling stomatal density Research Approach
Precision farming of wheat for future environments
The aims of this project are: Phenotyping leaf growth with respect to environmental influences in wheat and identify genetic loci controlling leaf growth
Design heterogeneous catalysts for asymmetric catalysis
The aim of this general project is to design materials that have the right functional groups at the molecular level to induce enantioselectivity in organic reactions. If successful, it might change how we think of organic chemistry and will allow to include solids in the organic chemistry toolbox.
Modelling algorithms underlying animal decision-making
Animal models are tools to investigate brain mechanisms and how they are affected by neural interventions. The goal of this project is to develop a model simulating a mouse freely moving in an experimental cage. It will consider various simple behavioural rules and will be implemented in Matlab
Piezoresistive behavior of polymeric cantilevers based on the integration of nanowires
Semester or Master project to develop the fabrication process of the piezoresistive polymeric cantilever and characterization of the electromechanical behavior
Optimize efficiency for interacting airflows of an omnidirectional MAV
In omnidirectional MAVs with tillable rotors, the airflow interference between propellers can drastically reduce the platform efficiency. Within this project, the effect of external airflow on the propeller performance will be analysed, and a method to improve the performance will be proposed.
Sonification of interaction forces in climbing: What is applicable?
As interaction forces in climbing have not been sonified so far, the aim of this project is to elaborate how performance metrics can be represented in sound dimensions and how much information can be displayed so that the climber can benefit from it.
PhD student in Structural Biology by NMR
A Phd student position is available at the Biozentrum Basel in the group of Stephan Grzesiek. Our aim is to apply and develop modern NMR methods for obtaining structure, dynamics, and function information on biomacromolecules and their complexes.
Design and Control of a Bicopter MAV
Design and control of a UAV using only two rotors, and additional actuation to allow for full position and orientation controllability.
Assessment of different handles for intuitive teleoperation of a robotic endoscope
In this project, you will support our interdisciplinary team in the development of a minimally invasive robotic endoscope for cutting bone with laser light. The goal of this thesis is to design and perform a user study assessing different handle prototypes for a commercial teleoperation device.
Deep Learning for Semantic SLAM
The goal of this project is to train a deep neural network to segment robot sensor data (vision / LiDAR) into semantic scenes. The segmentation is then used to facilitate the SLAM process.
Development of vesicles for localized treatment of psoriasis
Psoriasis is a chronic inflammatory skin disorder that drastically impairs the quality of life of patients. Nowadays topical therapy is the most commonly used initial treatment but conventional formulations serve the purpose only to a limited extent. Therefore, novel treatment approaches are urgently needed. The aim of the project consists in developing vesicles able to penetrate transdermally and elicit a targeted localized effect. Vesicles are developed to maintain the drug active over time, to facilitate its penetration through the skin and to deliver the active compound to the specific area. To achieve a continuous supply of drug over time, drug carriers are embedded into electrospun fibers which are expected to progressively degrade and release the vesicles continuously.
Computer Vision for Robot cooperation
Navigating a ground robot in a disaster response scenario is a difficult task. The aim of this project is to use drones to follow a ground robot and extend its field of view for operation in dangerous disaster response scenarios.
Segmentation of Tree Parts from Pointcloud data using Deep Learning
The goal of this project is to develop a neural network framework that can segment the point cloud of a tree into its components, namely trunk, branches and leaves. This project will closely follow a recent work, PointNet, which performs segmentation using point clouds as input.
Help our Athletes win Gold at Tokyo 2020!
* Modelling Human Multi Body Dynamics * Parameter Identification * Optimizing Athletic Performance and Aerodynamics * Support the best Swiss Paralympic Wheelchair Athletes: Marcel Hug and Catherine Debrunner
Support ongoing research in climbing (internship)
This opportunity is an internship in the field of climbing related research. It is available for prospective Human Movement Scientist or Sport Engineers
Excited State Dissolved Organic Matter Reactivity with Sulfa Drugs
Triplet excited dissolved organic matter (3DOM*) is as an important photo-produced reactive intermediate that impacts pollutant and carbon cycling in natural waters. Sulfonamide antibiotics (sulfa drugs), a class of wide-use pharmaceuticals that eventually make their way into our water sources, have been shown to be degraded by DOM. However, conflicting reports of reactivity when using DOM from different sources (e.g. microbial- vs. plant-derived) have created some open questions. The goal of this master’s thesis is to better understand the reactivity of DOM with sulfa drugs as a function of DOM source. The project will utilize time-resolved laser spectroscopy to probe these questions. Candidates that are interested in mechanistic organic chemistry, environmental fate of pharmaceuticals, and photochemistry should apply.
Surface treatment of 3D-printed parts with acetone vapor
Building a "Desktop Polisher" for defined acetone vapor polishing of parts printed by fused deposition modeling (FDM). Subsequent optimization of polishing parameters for optimum surface quality and water resistance of treated parts.
Reduction of Edge Effects in Composite Lattice Core Sandwich Structures through Topology Optimization
The objective of this thesis is to study the reduction of edge effects in composite lattice core sandwich structures by optimizing the topology of the lattice core, in order to increase the global structural performance under out-of-plane compression loading.
Measuring Surface Forces of Oil Droplets with a Fluidic Force Microscopy System
This project aims to establish a measuring system for the investigation of surface forces of oil droplets. The system is based on a combination of atomic force microscopy (AFM) and microfluidics, that enables the formation, reversible attachment and manipulation of oil droplets in the micrometre siz

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