Available Theses
Thesis in Industry - Starting ASAP!
ETH Zürich's Exploration Lab is partnering with Siemens - developer of intelligent technologies that connect energy systems, buildings, and infrastructure - to offer a unique thesis opportunity. You'll have the freedom to choose from a diverse range of real-world projects across multiple domains, based on your individual interests.
Keywords
usability, high-tech, rapid prototyping, sustainability, industrial automation, mechanical design, mechanical engineering, automation, process design, robotics, machine learning, applied AI, food processing, advanced materials, agile, development, product development, control
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Semester Project , Master Thesis
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Published since: 2026-08-13 , Earliest start: 2026-02-15 , Latest end: 2026-09-12
Applications limited to ETH Zurich , EPFL - Ecole Polytechnique Fédérale de Lausanne , Zurich University of Applied Sciences
Organization pd|z Product Development Group Zurich
Hosts von Salis Marco
Topics Information, Computing and Communication Sciences , Engineering and Technology
Design Engineering at AUDI F1
Audi F1 and the Exploration Lab are looking for a design engineer willing to work on high-risk, high-reward topics. The topics are top-secret but might just change the course of a race.
Keywords
usability, pcb design, high-tech, rapid prototyping, sustainability, industrial automation, mechanical design, mechanical engineering, automation, process design, robotics, machine learning, applied AI, food processing, advanced materials, agile, development, product development, control, material science, computer science, electrical engineering, programming
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Semester Project , Course Project , Internship , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2026-08-13 , Earliest start: 2026-09-14 , Latest end: 2027-03-31
Applications limited to ETH Zurich
Organization ETH Exploration Lab
Hosts von Salis Marco
Topics Information, Computing and Communication Sciences , Engineering and Technology
Topology Optimization for Induction Heating Applications
Topology Optimization (TO) is well established for structural applications, where structures are optimized regarding their mechanical properties under volume constraints. Unlike shape optimization, TO is free from initial structure assumptions and can propose fundamentally new geometries. This would also be interesting for induction heating (IH) applications, where the design of magnetic cores and copper coils need to be optimized. However, topology optimization is much less established in the field of electromagnetic heating.
Keywords
Topology Optimization, Inductive Heating, Electromagnetics, Copper Coil, Magnetic Core, Flux Concentrators
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Master Thesis
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Published since: 2026-08-10
Organization pd|z Product Development Group Zurich
Hosts Ritter Simon
Topics Engineering and Technology
Benchmarking Additive Manufacturing Processes for Copper Induction Coils
Additive manufacturing (AM) of copper offers great advantages in the production of copper coils used for inductive heating. Without the constraints of conventional manufacturing techniques (bending, milling, soldering, etc.) there exist huge potential for optimization. However, AM of copper comes with its own challenges. Material properties often do not reach the absolute values of pure copper, and each additive manufacturing process comes with its own design guidelines, many of which are not yet fully established for the application of induction coils.
Keywords
Additive manufacturing, 3D printing, LPBF, MBJ, MEX, copper, induction heating
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Master Thesis
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Published since: 2026-08-10
Organization pd|z Product Development Group Zurich
Hosts Ritter Simon
Topics Engineering and Technology
Learning Task Structure from Multimodal Human Demonstrations
Expert knowledge in procedural tasks such as surgery or assembly involves more than knowing which action is performed. Tool trajectories, relative poses, alignment of components, and resulting states can be essential to understanding a procedure. This project uses multimodal recordings from an orthopedic surgery training task, including synchronized video and 6D instrument poses, to investigate how such measurable process knowledge can be extracted from a small number of human demonstrations and combined into a structured representation.
Keywords
Computer Vision, Learning from Demonstration, 6D Pose, Multimodal Sensing, Procedural Understanding, Human Demonstration, Geometric Reasoning, Foundation Models, Surgical Training, Knowledge Capture, Pose Estimation, Robotics
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2026-08-10 , Earliest start: 2026-08-23 , Latest end: 2027-02-14
Organization pd|z Product Development Group Zurich
Hosts Hogenkamp Maarten
Topics Information, Computing and Communication Sciences , Engineering and Technology
Development of a Physical Engineering Benchmark to evaluate Text-to-CAD AI Systems
Text-to-CAD AI systems increasingly generate 3D models from natural-language descriptions, yet their ability to produce manufacturable and functionally effective engineering designs remains insufficiently understood. This thesis develops and validates an Engineering Benchy: a standardized, physically testable benchmark for assessing AI-CAD capabilities from valid model generation and manufacturability to functional performance and advanced design quality.
Keywords
AI | CAD | Text-to-CAD | Additive manufacturing | Product development | Prototyping and physical testing
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Semester Project , Bachelor Thesis , ETH Zurich (ETHZ)
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Published since: 2026-08-10
Applications limited to ETH Zurich
Organization pd|z Product Development Group Zurich
Hosts Bürkli Julian
Topics Engineering and Technology
Action Segmentation for Assembly Workflow Understanding
Understanding how people perform assembly operations is important for process analysis, documentation, training, and assistance. Supervised temporal action segmentation can divide long videos into procedural steps accurately, but depends on costly frame-level annotations and fixed action classes. This project compares supervised, unsupervised, and zero-shot approaches for segmenting assembly workflows and investigates when task descriptions and physical measurements can reduce the need for manual labels.
Keywords
Computer Vision, Temporal Action Segmentation, Unsupervised Learning, Vision–Language Models, Egocentric Video, Assembly, Open-vocabulary Recognition, Physical Grounding, Weak Supervision, Workflow Understanding
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Semester Project , Bachelor Thesis
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Published since: 2026-07-27 , Earliest start: 2026-08-01 , Latest end: 2027-01-31
Organization pd|z Product Development Group Zurich
Hosts Hogenkamp Maarten
Topics Information, Computing and Communication Sciences , Engineering and Technology
Automatic Object-to-Marker Pose Estimation
Understanding how tools and objects move and interact is important for automated workflow analysis and process documentation. Marker-based 6D pose estimation accurately measures an object’s position and orientation, but typically tracks only the attached marker rather than relevant object features. This project explores how state-of-the-art computer vision methods can automatically establish this relationship using only a few images or a short monocular video, reducing calibration effort and simplifying the integration of new objects.
Keywords
Computer Vision, 6D pose estimation, Tracking, Object tracking, Transformers, Calibration, Deep Learning, Few-shot learning, Workflow understanding
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Semester Project , Master Thesis
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Published since: 2026-07-20 , Earliest start: 2026-08-01 , Latest end: 2027-02-01
Organization pd|z Product Development Group Zurich
Hosts Hogenkamp Maarten
Topics Information, Computing and Communication Sciences , Engineering and Technology
Master Thesis in Industry: Turn Deep Tech into Real Business
Don’t analyze a case from 2015 — build the business case, run the customer discovery and de-risk a real product with a real company. This is where technology becomes a business. You will sit between brilliant engineering and a real market with a diverse team of various backgrounds.
Keywords
innovation management, business model, business development, go-to-market, customer discovery, market analysis, market sizing, unit economics, financial modeling, pricing strategy, value proposition, technology transfer, commercialization, entrepreneurship, startup, venture, deep tech, B2B, product management, strategy, lean startup, MVP, circular economy, supply chain, Industry 4.0, sustainability strategy, willingness to pay, agile, scale-up
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Internship , Master Thesis
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Published since: 2026-06-08 , Earliest start: 2026-09-14 , Latest end: 2027-03-31
Organization pd|z Product Development Group Zurich
Hosts von Salis Marco
Topics Engineering and Technology , Economics , Commerce, Management, Tourism and Services
FactoryNet: Training Data and Foundational Models for Industrial AI
Unplanned downtime costs manufacturers $2.3M per hour, yet no open dataset connects sensor telemetry to structured fault diagnosis at scale. Forgis is building HYPERION, the first foundation model for cyberphysical systems (EUR 3.8M funding,$500kcompute credits). FactoryNet is its training data engine — 1M+ causally-structured, multimodal episodes spanning 15+ machine types — just awarded 50,000 GPU-hours on CSCS Alps through the Swiss AI Initiative.
Keywords
Robotics, Control, AI, Foundation Model, Industrial Automation
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Master Thesis
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Published since: 2026-05-18 , Earliest start: 2026-05-31 , Latest end: 2027-05-31
Organization pd|z Product Development Group Zurich
Hosts Gimeno Lucas
Topics Engineering and Technology