Student Research Projects and Master Theses at SCS


Are you studying electrical engineering, informatics, physics or mathematics? Are you inquisitive, communicative and motivated, and never tire of learning? With SCS, you will have the opportunity to realise your student research projects or master thesis. The work is normally shared between two people, or in exceptional cases covered by one person. It should include a research and development component.

If you already have your own idea for your student research project or master thesis, and you have the support of your professor, get in contact with us. Otherwise, let the following ideas give you some inspiration. We will help you transform these ideas into something concrete.

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Possible Student Research Projects and Master Theses

  • Automatisierte Anamnese von Heizungen und GebäudeenergieanlagenAutomatisierte Anamnese von Heizungen und Gebäudeenergieanlagen

    In der Schweiz besteht ein grosses Energieeffizienzpotential in Gebäuden. Bestehende Heizungsanlagen in Gebäuden sind heute oft nicht ideal eingestellt, weisen Mängel auf oder sind gar dysfunktional. Zur Detektion dieser Mängel soll ein Prototyp eines automatisierten Anamnese-Systems aufgebaut werden, welches aufgrund von sensorischen Messgrössen (primär Temperaturfühler) die Anlage erstens identifiziert, zweitens auf Fehler analysiert und drittens eine Liste von Handlungsempfehlungen generiert, um das System zu verbessern.

  • Flexible FPGA-based Test Equipment to Model and Characterize the Real-Time Behavior of an Ethernet RingFlexible FPGA-based Test Equipment to Model and Characterize the Real-Time Behavior of an Ethernet Ring

    In this work, flexible test equipment for Ethernet network hardware and firmware shall be evaluate and commissioned. The goal is to model and characterize an Ethernet network based on BroadR-Reach with ring topology and HSR protocol for its real-time behavior.The test equipment could be based on devices available at Extensions may be developed to further improve functionality.

  • Software-Architecture for SDRSoftware-Architecture for SDR
    Alle aktuellen SDR Softwarepakete haben Einschränkungen. Es gibt GNU Radio, welches kompliziert und schwierig zu bedienen ist, und es gibt verschiedene SDR GUIs, welche jedoch nicht einfach erweiterbar sind. Das Ziel ist eine einfach zu bedienende Software zu erstellen, welche es ermöglicht, Radiosignale zu analysieren und Algorithmen auszuprobieren. Fertige Abläufe sollen dann auf Knopfdruck in eine C-Datei exportiert werden können, um eine Integration in Embedded Systeme so leicht wie möglich zu gestalten.

  • Decentralized Ledger eVoting SystemDecentralized Ledger eVoting System

    eVoting is an unsolved problem, mainly because of security concerns connected to centralized IT systems. Blockchain technology enables new ways to solve IT problems in a transparent, tamper-proof and decentralized way. However, scalability of such solutions is still unsatisfactory and there’s still no solution that provides privacy of the single voter and transparency of the overall voting process at the same time.This master thesis aims at implementing a voting solution that scales to Swiss national votes. The technologies to be used could include zero knowledge proofs (zk-SNARKS), homomorphic encryption and smart contracts on a public blockchain (i.e. ethereum). Different layer-two technologies shall be evaluated to provide scalability for this use case.

  • Students Internships AI-based Golf-Coach with Automated Swing AnalysisStudents Internships AI-based Golf-Coach with Automated Swing Analysis

    Der Golfschwung gilt als einer der komplexesten Bewegungsabläufe aller Sportarten. Für den Amateurgolfer besteht die Schwierigkeit darin, bei einem Fehlschlag den Fehler in seiner Bewegung zu erkennen und entsprechend zu korrigieren.

    Ziel 1: Entwicklung einer Physik-Engine mit geeigneten Parametern für die Berechnung der Flugbahn des Golfballs.

    Ziel 2: Automatisierte Analyse des Bewegungsablaufs des Golfspielers und gezieltes Erkennen fehlerhafter Muster. Dazu soll ein geeignetes Verfahren ausgewählt und umgesetzt werden, wie z.B. Vergleichen mit Bewegungsabläufen von Profis.

    Der Simulator soll mit Low-Cost COTS Komponenten aufgebaut werden.

  • Towards User-independent 2D / 3D Object Classification of Complex Life Science ImagesTowards User-independent 2D / 3D Object Classification of Complex Life Science Images

    We develop novel machine vision & mathematical morphology algorithms to analyze complex multi-modal Life Science images.

  • Transfer Learning for Image Segmentation using Convolutional Neural NetworksTransfer Learning for Image Segmentation using Convolutional Neural Networks

    Today’s Machine Learning (ML) success is often limited by a lack of labelled ground truth (GT) data to train the models. This is especially true for applications in medical imaging.Transfer learning (TL) is a state-of-art ML-technique that can be useful to overcome this problem for similar yet distinct tasks. TL tries to apply knowledge or models gained from a task to a second one. In the field of image recognition, TL-methods for deep neural nets re-use parameters trained on source domain data except for the output layer (see image on the right).In medical optical coherence tomography (OCT) of the eye only a limited set of GT-labeled images exists. In addition, there are several device manufacturers and imaging approaches. Thus, transfer learning could 1) enable an easier addition of new device types or imaging techniques, 2) improve the quality of available segmentations even with limited data.

  • Virtual Reality as 3D Ground Truth Generator for AI, Machine Learning and Deep LearningVirtual Reality as 3D Ground Truth Generator for AI, Machine Learning and Deep Learning

    Training effective Artificial Intelligence (AI) algorithms today often requires large amounts of ground truth data. Typically, this is a laborious, costly and time-consuming process often requiring manual adjustment. These problems can be overcome by combining AI with Virtual Reality (VR): an emerging technology with various applications in medicine, training, business and simulation. VR creates artificial environments that often resemble our real world.This project aims at exploring the potential of VR as 3D ground truth generator for state-of-the-art Machine Learning (ML) and Deep Learning (DL) Algorithms.