Develop an innovative startup concept that solves a real-world problem! You will work in small teams to design entrepreneurial solutions integrating technological feasibility, sustainable business models, and active stakeholder engagement. This open-ended micro-module gives you the opportunity to explore pressing issues such as climate resilience, the circular economy, health technology, mobility, and digital inclusion, and to translate your ideas (for example from former ECIU Challenges) into actionable business concepts. The micro-module is a collaboration between Hamburg University of Technology, University of Twente and University of Stavanger as an associated partner.

Expected impact:

The concepts developed during the micro-module may serve as the foundation for real ventures in the future, either within or beyond the university ecosystem.

Additionally, the module empowers students to:

- Apply entrepreneurial methods in a real-world context

- Gain critical insights into the startup lifecycle, from ideation to go-to-market

- Build collaboration, leadership, and innovation capabilities

- Understand the challenges of technology transfer and commercialization

Participants will walk away with a toolkit of entrepreneurial skills and mindsets applicable across sectors and disciplines, giving them the confidence to take initiative in complex, uncertain environments.

CV (Curriculum Vitae) is a document that summarizes your educational and professional history. It must provide a detailed overview of your academic and work experience, skills, achievements, and qualifications.

Motivation letter is a personal statement and it might include a brief introduction of yourself, explanation why are you interested in the learning opportunity you are applying to, any relevant experience or skills that you have, your goals and how this opportunity will help you achieve them, This document should not be more than 400 words.

Motivation Letter

Hamburg University of Technology

Innovation to Impact: Empowering Startups to Solve Real-World Problems

Technology Transfer and Entrepreneurship with a Focus on Technological Innovation

Entrepreneurship, technology and innovation

Critical and innovative thinking

Inter-personal skills

Media and information literacy

Intra-personal skills

Arthrogryposis Multiplex Congenita (AMC) is a congenital condition characterised by multiple joint contractures, stiffened or fixed joints, and reduced active range of motion. Children with AMC can have difficulties performing everyday activities that many people take for granted. Depending on the individual, activities such as eating, drinking, dressing, brushing their teeth or playing may require assistance from a parent, caregiver or therapist.

Current orthoses for AMC are largely passive. They can support and position a limb, but they do not actively assist movement. To address this limitation, a project at TUHH is developing an ultralight, motorised elbow orthosis designed to actively assist arm movement. 

You will receive information about the orthosis, its capabilities and the challenges faced by its potential users. From there, teams are invited to develop their own ideas and solutions from their different backgrounds and perspectives.

**There is no single correct solution. The goal is to explore how a motorised orthosis could become a meaningful tool for greater independence.**

Transcript of Records is an official document issued by your home university. It specifies the name of the institution, the academic programme you are enrolled in, the list of courses taken up until the current period, the exams or tests you passed, the grades and the credits you earned. 

Transcript of Records

A laughing child is riding a bike and has a prosthetic forearm. AI-generated picture.

From Movement to Independence: Designing Assistive Technology for Children with AMC

Resilient communities

Artificial Intelligence (AI) is a field of rapid innovation and set to fundamentally transform numerous domains. In this context, we are confronted with significant ethical challenges, for example with respect to issues like fairness, bias, autonomy, disinformation, sustainability, safety, and human-machine interaction. In this Challenge, participating students practically explore how innovation in AI development can be aligned with ethical standards. The focus on ethical AI innovation is especially well-suited to CBL, as it involves complex sociotechnical questions that demand creative, experimental, and interdisciplinary thinking and collaboration. The Challenge also provides insights into the functioning of AI, with a special focus on generative models, and conveys important concepts and frameworks from inclusive design theory, innovation theory, and technology ethics. By interacting with a diverse set of external stakeholders, students gain insights into different domains and industries.

Artificial Intelligence autonomous vehicles

Ethical Innovation and Artificial Intelligence

Global citizenship

The module is divided into three parts:

- background knowledge,
- simulation and experiments, and
- theoretical analysis.

The goal is to provide a holistic understanding of the manifold challenges associated with communication in Industry 4.0 and how IEEE 802.15.4 standard addresses these.

The concepts learned in the introductory lectures will be directly applied in simulations using open-source software, as well as experiments with a real hardware.

Team-based assignments help you both deepen your understanding of the modern communication technology and improve collaboration skills. Finally, analytical evaluation explains how to compute fundamental performance bounds and validate Quality-of-Service for existing and upcoming applications, turning you into a fully-equipped network specialist.

a large room with many lights and a large statue

Enabling Industry 4.0

Get in touch with Industry 4.0 challenges (spring 2026)

Engineering students often encounter Systems Engineering only in abstract terms. SE-CHOC makes systems thinking tangible by embedding it in a concrete, motivating use case: converting a 3D printer into a chocolate printer. The micromodule emphasises learning by doing, reflection and structured reasoning rather than technical optimisation.  

**What you will do:**

- Analyse and discuss stakeholder expectations and system constraints
- Develop and adapt system architectures
- Work in defined engineering roles
- Model and visualise systems and interfaces systems and interfaces
- Respond to scenario-based changes
- Reflect on decisions and teamwork

SE-CHOC: transform a conventional 3D printer into a functional chocolate printer

Understand and apply core Systems Engineering principles

Circular economy

Experimental sciences are increasingly shaped by digital technologies, automation, and data-driven research. In chemical and bioprocess engineering, experimental data is essential for understanding reaction mechanisms, optimizing processes, and developing sustainable technologies. However, many datasets generated in laboratories remain difficult to reuse beyond their original project. Data may be stored in incompatible formats, lack sufficient metadata, or be documented in ways that prevent reproducibility.

The **FAIR principles**—Findable, Accessible, Interoperable, and Reusable—provide an important framework for improving the quality and usability of research data. FAIR data management practices make datasets easier to discover, interpret, and exchange between researchers, institutions, and digital tools.

However, FAIR alone is often not sufficient. As scientific workflows increasingly rely on machine learning, simulation, and automated data analysis, datasets must also become **XAIR: Explainable and AI-Ready**. This means that data must be sufficiently structured, contextualized, and documented to allow algorithms and researchers to understand how it was generated, what it represents, and how it can be reliably used in computational models.

This ECIU micro-module introduces students to these emerging challenges in **research data management and data literacy** through a hands-on learning experience. Using a biocatalysis case study from chemical and bioprocess engineering, students will follow the lifecycle of research data—from experimental generation to data structuring, semantic enrichment, and analysis. By working with real datasets, participants will explore how well-managed data enables reproducibility, interdisciplinary collaboration, and new research opportunities such as modeling, digital workflows, and AI-supported analysis.

FAIR & XAIR Data Literacy

... with a focus but not only in Chemical and Bioprocess Engineering

**Unlock Your Agile Leadership Potential!**  
Step into the role of an agile team leader and discover what it takes to guide innovation in complex engineering challenges. Over one semester at TUHH, you will lead real teams, master agile practices, and reflect on your own leadership journey – preparing you for the next step in your career.

Agile methods are widely used in engineering practice, but leadership in agile contexts is often missing in the curriculum.  
In this challenge, you will:

- Form and lead teams applying agile practices to real cases.
- Develop strategies for decision-making, facilitation, and conflict resolution.
- Reflect on the role of leadership in agile environments.
- Experience cross-cultural collaboration in a truly international environment.

By combining **product development challenges** with **the responsibility of leading a team**, you will train both technical understanding and agile leadership skills.

five people sitting around a billiard table and discuss a ball-push unit

Leading Agile Teams

Train leadership by leading agile teams yourself!

This interdisciplinary,  course invites students to design a sustainable waste valorization process that transforms industrial or other useful wastes into chemicals, fuels, or energy. In response to the global need for circular, climate-neutral technologies, the course challenges participants to reimagine waste streams not as a disposal problem, but as a valuable resource for future chemical production.

At the start of the course, each team of four selects a waste feedstock — such as used tires, petroleum coke, unsorted or mixed plastics, or residues from the pulp and paper, agricultural, or bio-energy industries — together with a target product that can be obtained from it. Based on this choice, the teams develop a custom-tailored process route that relies on chemical or energy conversion pathways beyond ordinary combustion, addressing both technical and sustainability aspects. As additional context, teams are asked to consider the boundary conditions of Norway, the host country of the upcoming ESCAPE-37 conference, for instance with regard to available energy sources.

Over the course of several weeks, students explore topics such as Waste-to-X conversion routes, conceptual process design (including biodiesel production as a worked example), process modelling beyond standard simulation tools, and production scheduling. They engage in activities like resource and reaction-pathway selection, process simulation and synthesis, energy and material balancing, energy system integration, and the calculation of key performance indicators (KPIs) and life cycle assessment (LCA) results to evaluate technical, economic, environmental, and societal impacts.

A distinctive feature of the course is its strong focus on applied knowledge, international collaboration, and industrial relevance. Teams are formed across institutions, encouraging students to practice working in international, multidisciplinary settings. A mock-presentation session with peer feedback helps teams prepare for their milestone presentations, and structured consultations together with status-report milestones support the iterative development of each project and its internal scheduling for the remaining weeks.

The course concludes with a written report and a final presentation to a jury, where teams pitch their process concept and defend its feasibility, innovation, and sustainability. This simulated professional setting fosters confidence in presenting complex ideas to diverse audiences.

In addition to the academic experience, the course offers an optional opportunity to submit the final project to the EURECHA Process Design Contest 2027, organized by the European Committee for the Use of Computers in Chemical Engineering Education (EURECHA) together with the Computer-Aided Process Engineering (CAPE) Working Party and the Energy Section of the European Federation of Chemical Engineering (EFCE). This year's contest challenge — utilization of industrial or other useful wastes to chemicals, fuels or energy — directly builds on the course's project theme, allowing students to present their work to a broader international audience, receive mentoring from EURECHA or the contest's sponsor AVEVA, and gain recognition, with the possibility of monetary prizes and an invitation to present at ESCAPE-37 in Trondheim, Norway.

students sitting around a table and working with their mobile devices or pen and paper to do a project together

Sustainable Process Design Project

Chemical plants can have every shade of green  - in theory. Let`s try and find out how far we can push it.

The construction sector is one of the largest industries worldwide, yet construction processes remain largely manual, fragmented, and characterized by limited automation. Many construction activities are repetitive and safety-critical, leading to productivity constraints and increased risks for workers. At the same time, growing project complexity, labor shortages, and sustainability requirements demand more efficient and intelligent construction methods. The systematic identification of automation potentials and the integration of robotics and artificial intelligence into construction processes is therefore a central challenge for the future of the built environment.

Robotics combined with advanced perception and AI-based decision-making offers a promising pathway toward safer and more productive construction workflows. Vision-based systems using RGB and infrared sensors enable robots to perceive dynamic construction environments, while AI-driven methods, including multi-modal large language models, support scene representation and task planning. Approaches towards localization, navigation, and motion planning further allow robotic systems to operate autonomously in multi-robot teams or in collaboration with human workers. However, successful implementation requires rigorous scientific methodology, structured problem formulation, and critical engagement with existing research.

The ECIU micromodule, embedded in the course *Scientific Working in Engineering*, addresses the aforementioned challenges within a challenge-based learning framework focused on construction robotics in the built environment. Students work in international and multidisciplinary teams to systematically analyze construction processes and identify repetitive or safety-critical tasks with automation potential. Based on the analysis, students define a robotic use case and concept, which is explored through literature research, critical source evaluation, and structured scientific writing. The reflective and responsible use of AI tools in research is an integral component of the course.

Building on a literature-based problem formulation and project plan, the teams develop and implement a simulation-based solution to the selected robotic use case. An agile framework structures the collaboration, particularly during a dedicated experimental mobility phase in which robotic concepts are prototypically implemented and monitored. The course is conducted in hybrid formats and integrates participants from different partner institutions, concluding with the presentation of results.

Scientific working in engineering

An introduction to smart robotics in construction

Following the success of the first Everyday Heroes Challenge, TU Hamburg and the Elfenwiese School continue their collaboration to further improve everyday life for children with special needs.

Every child experiences school differently. Some require physical assistance, others benefit from adapted learning materials, sensory tools, or improved spaces for communication and interaction. Together with teachers, physiotherapists, and university experts, participants will identify these needs and develop practical solutions that can make a genuine difference.

Whether you contribute on-site in Hamburg or remotely from another ECIU university, you will become part of an international team that combines engineering, creativity, education, and social responsibility. Together, you will create solutions that have the potential to improve everyday life well beyond the duration of the challenge.

Facilitators from the participating TU Hamburg units form the interdisciplinary Teamcher Collective, supporting participants throughout the challenge with methodological guidance, technical expertise, continuous feedback, and educational perspectives.

**Why Join?**

- Work on a real challenge with real users.
- Experience interdisciplinary collaboration with students from across Europe.
- Learn how engineering and design can create meaningful social impact.
- Develop a prototype that may continue to benefit the school community beyond the challenge.
- Gain practical experience in design thinking, rapid prototyping, and digital fabrication.
- Become part of an established ECIU Challenge entering its second edition.

Child with superman cape walking along a street

Everyday Heroes: Innovating Assistive Tools for Children with Special Needs

(winter term 26/27)

The 3 ECTS project, done in hybrid mode and with mixed teams of students from TUHH as well as from ECIU partners, will be embedded in an existing 6 ECTS PBL class addressing mobile robots under real world uncertainty. The institute has mobile robots and sensors available for use both on water and on land. This year we plan working on small sailing drones. Robots, code, and data from previous field trials are available and will be explained as a basis for this years project. A short lecture series will introduce basic robotics and computer vision concepts and explain the actual robot setups and the problem statement in more detail. The focus in terms of content and intended learning objectives is on object recognition on embedded systems. Object recognition on embedded systems poses specific technical challenges that differ from those encountered on powerful desktop or server hardware. In embedded systems, energy-efficient algorithms and hardware are crucial for maximizing runtime. For applications such as collision avoidance, object recognition models must work in real time, simultaneously (at least in the setups available to us) with noisy or low-resolution sensor data and must function reliably under different lighting conditions, weather conditions or perspectives. The complexity of the task requires expertise from several fields of study, and interdisciplinary collaboration is not only useful but often necessary for object recognition on embedded systems. ECIU students will be part of student teams and work with data to develop an approach to detect other robots and obstacles using deep learning methods. The focus will be on selecting existing methods suitable for object detection on an embedded platform. A key aspect will be evaluating and tuning the methods to achieve sufficiently fast and reliable object detection.

Intelligent System Lab

Explore the world of mobile robots!

In this micro-module, you are challenged to design an educational escape room that teaches the core principles of Challenge-Based Learning (CBL): Engage, Investigate, and Act. The escape room will serve as a hands-on tool for educators seeking to implement CBL effectively in their own classrooms.

Member university

Hamburg University of Technology

Member university

Hamburg University of Technology

Learning opportunities of Hamburg University of Technology