Practical experience
Landing a job takes more than talent, it takes action. Demola gives you the chance to tackle real challenges, collaborate with others, and build proof of what you can do even when things are uncertain. By actively participating in a Demola project, you can turn your skills into competencies and concrete experience.
Partnered with Innovative Companies
Our platform, created together with leading companies and professors, connects you to real-world innovation projects. You’ll work as part of a team on an innovation and development project, guided by Demola’s expert facilitators. Participating in a project will give you practical experience and the confidence to deal with complexity in any job.
At Demola, innovation projects are built around real-world project topics co-designed with companies and public-sector organisations. If selected, you'll join an innovation team working to develop meaningful solutions that respond to validated needs.
Our projects tackle complex, relevant problems grounded in industry and societal needs. You'll work in a team to design and demo solutions, benefiting from the insights and findings of previous Demola projects. Most Demola projects last around two months, but the exact duration depends on the programme they are part of.
Each team benefits from expert guidance through coaching sessions and facilitated community events. Demola's facilitators bring years of experience in innovation and adapt their support to match your ambition and commitment. You are expected to take an active role, both individually and as a team.
You'll co-create with other teams and Demola's experts, and validate and test your solutions with real stakeholders to continuously refine your approach. High-performing teams gain access to a network of professionals from Demola's industry partners for further input and exposure.
You'll build in-demand, career-ready skills in creative problem-solving, AI-assisted innovation, project management, international collaboration, and resilience - all while working in an environment that mirrors real innovation practices.
Your team owns the outcomes created during the project. Use them in job interviews, your portfolio, a Master's thesis, or even as the foundation of a startup. In some cases, your work may also earn you academic credit (ECTS) if you are a student.
The impact
Ready to turn your skills into competence? Our claims are backed by feedback from our community of participants and alumni.
Strongly agree (49.3%)
Agree (43.6%)
Neither agree or disagree (5.3%)
Disagree (1.3%)
Strongly disagree (0.5%)
2 272 people took part in the survey.
New skills
65.6%
Valuable work experience
63.9%
New friends
51.5%
Startup ideas
34.4%
International teamwork experience
30.5%
Industry contacts
23.9%
Self-esteem
23.9%
New motivation to study
22.8%
Confidence in career choices
20.3%
Researcher contacts
17.6%
Better position in the labor market
13.5%
Other
1.5%
Based on Q4/2022 survey
If you’re currently studying at or near one of our Demola locations or partner universities, you’re welcome to join a Demola project.
In our partner cities, the projects are also open to graduates and professionals who are exploring new career paths or interested in co-creating and launching startups in the future.
Many alumni have participated in more than one Demola project – the current record is seven. For active alumni, we facilitate further development in their academic studies or future careers:
Explore or fine-tune your Master’s thesis topic through a Demola project and find a potential industry collaborator for your Master’s thesis after the project.
Develop an expert profile that highlights your project contributions, as well as innovation and interpersonal skills. Top-performing participants will have their expert profiles shared and recommended within Demola’s partner network, verifying their skills and proactive mindset.
Build on your project results, connect with like-minded teammates, and use your entrepreneurial mindset to lay the groundwork for a startup.
Get onboarded with Demola
Create a Demola profile.
Browse project in your location and apply to those that interest you.
If you get selected, confirm your seat and start the teamwork.
Apply to one or more projects today!
Oulu
Future of Work
**The Challenge** Marine crews rotate. A new captain steps aboard a vessel they've never seen before. The previous captain spent six weeks getting to know the quirks of this specific ship — which cylinder always runs slightly hot, which fuel pump is finicky, which weather the engine room copes badly with. The handover is a brief in-person walkthrough plus a stack of paperwork, and then the new captain sails. Worse: expert advice given to one crew ("your equipment is acting strange — probably because of this") often never reaches the next one. At its core this is a communication problem — how do we make sure crucial information survives the handover? Handing the new crew a 20-page report and trusting they read it is not the answer. The same failure mode exists in any shift-rotation environment, from process plants to hospital shift changes. **The Data** The briefing draws on two layers. **Static data**: what is on board — equipment inventory, engine type and surrounding subsystems, reference materials and manuals (every vessel is different: a cargo vessel and a bulk carrier may share almost nothing, so "here is where to find the manual for this system" is already valuable). **Dynamic data**: what has happened — logbook entries, alerts and incidents from navigational and automation subsystems, and known-but-not-yet-resolved issues flagged by remote experts analysing the vessel's data in the cloud. **Mission** Build a crew-handover briefing generator, in phases. Start with the static layer: compile "here is what you're taking over" — equipment, reference links, manuals — into a single structured onboarding briefing, everything in one place. Then layer in the dynamic history: compress the most important crew-relevant patterns, incidents and open expert advisories into a briefing the incoming crew will actually absorb. Design the ingestion interfaces to be document-agnostic, so nothing in the pipeline depends on maritime data standards — the same engine should brief a hospital shift as easily as a ship's crew. Test the briefing format with experienced operators for clarity, trust and adoption. **Why we suggest this** Rotating crews lose institutional knowledge at every handover. Compressed, AI-generated briefings tailored to the specific equipment a new crew is taking over solve a problem that exists in any shift-rotation industry — vessels, process plants, hospitals, security operations. Underexplored as a product area. *Project will use AI-generated synthetic operational histories; anonymised real handover/incident report examples from the partner serve as a reference for structure and content.*
Apply by 27 Sept
Oulu
Healing the Planet
**The Challenge** Industrial service providers do clever technical work to make their customers' operations more efficient — saving fuel, reducing emissions, extending equipment life. But the customer in many cases is a corporate sustainability office or a shipping company's investor relations team. They don't speak in compression ratios and exhaust gas temperatures; they speak in CO2 tonnes, ESG ratings and regulatory compliance. Today, translating engineering wins into customer-facing sustainability narratives is a slow, manual, expensive job. Can AI do it automatically and credibly? **Mission** Build a system that takes engineering-level efficiency improvements (fuel saved, emissions reduced, equipment life extended) and generates customer-facing narratives at multiple audiences: ESG report contribution, investor relations talking points, regulatory compliance evidence. Validate the narratives for accuracy with engineers and for resonance with sustainability professionals. **Why we suggest this** The translation layer between engineering metrics and customer-facing sustainability narratives is a manual cottage industry across the industrial sector. Decarbonisation services and ESG reporting are fast-growing revenue areas; the supporting communications infrastructure is not. Strong cross-portfolio applicability across any B2B sustainability services business. *Project will use AI-generated synthetic engineering improvement data and publicly available ESG reporting frameworks.*
Apply by 27 Sept
Oulu
Byte-powered Future
**Background** When physical equipment misbehaves, its users face an uncomfortable choice: call an expert, or muddle through on their own. Calling an expert is expensive and slow — scheduling, travel and minimum call-out fees add up even when the fault turns out to be trivial. Muddling through risks making things worse, and can cross lines that void warranties or insurance ("open that screw and the warranty is gone"). Between these two options sits a middle ground: a guided diagnostic companion that gives users enough structured support to resolve straightforward issues themselves, stay safely inside the boundaries of what they are allowed to touch, and escalate intelligently when the problem is beyond their reach. That an LLM can extract troubleshooting steps from an unstructured manual is no longer the question — of course it can. The question is *repeatable, constant quality*: the same fault must produce the same verified guidance every time. A promising pattern: the system drafts step-by-step procedures from the manual, an asset expert verifies the draft, and the verified draft becomes a fixed instruction set the AI then follows — combining LLM flexibility with expert-controlled reliability. On top of the official manual sits a second layer worth capturing: the experiential knowledge of seasoned technicians ("give it a light knock before opening that screw, it comes loose easier"). To keep the focus on this hard problem rather than on learning how industrial machinery works, the project is deliberately set on a familiar class of physical assets — home appliances such as dishwashers, washing machines or AC units— as a stand-in for industrial equipment. The mechanics transfer directly to industrial field service. **Problem** Key questions to be answered in the project: - How can an LLM-based guide produce repeatable, constant-quality troubleshooting from unstructured manuals — same fault, same steps, every time? - What does the expert-verification workflow look like in practice: how are drafted procedures reviewed, locked as instruction sets, and kept up to date? - How should the interface communicate safe boundaries — what the user may and may not touch, where warranty and insurance limits run — without frustrating the user, while actively preventing harmful interventions? - How can experiential technician knowledge be captured and layered on top of official manuals? - What happens when the user gets stuck mid-procedure (step 4 fails)? How does the system genuinely take that feedback into account — re-plan, offer alternatives, or escalate to a human — rather than repeating itself? **In this project we aim to...** - Build a guided troubleshooting prototype for a familiar physical asset (e.g. a household appliance), driven by its real user and service manuals. - Implement and evaluate the draft → expert verification → fixed instruction set pipeline, measuring repeatability and guidance quality across repeated runs of the same fault. - Design the boundary and escalation model (safe vs. restricted interventions, when to hand over to a professional) and the mid-procedure feedback loop.
Apply by 27 Sept
Oulu, RAIDE portfolio
Future of Work
BackgroundLarge organisations make decisions constantly, but rarely see their consequences clearly. A choice made in sales affects operations; a change in R&D timelines ripples into HR and finance; a procurement decision reshapes logistics months later. These interdependencies are understood intuitively by experienced staff but are almost never mapped explicitly — which means that when a decision goes wrong, the causal chain is reconstructed in hindsight rather than anticipated in advance. The result is a recurring pattern: decisions that looked reasonable in isolation produce outcomes that surprise everyone 12 to 18 months later. A simulation environment that makes these interdependencies visible and explorable before commitment could fundamentally change how organisations reason about consequential choices. The "fake company" framing — using synthetic data rather than live organisational data — removes political sensitivity and lets participants experiment freely with scenarios that would be too risky or too controversial to test in reality.ProblemKey questions to be answered in the project:How can the causal dependencies between organisational functions be identified and mapped reliably enough to serve as the foundation for a simulation?What level of model fidelity is needed for a simulation to produce outputs that experienced staff recognise as plausible — and what simplifications are acceptable without losing credibility?Which decision types benefit most from simulation — where is the gap between intuitive reasoning and modelled reasoning largest?How should the simulation surface uncertainty and model limitations so that users develop calibrated trust rather than over-relying on its outputs?In this project we aim to...Produce a validated dependency map of a fictional organisation by applying decision archaeology: identifying one recurring, high-stakes decision type and reconstructing its causal effects across functions through structured interviews and workshops.Build a simulation layer on top of the dependency map that allows users to run "what if" scenarios and observe how decisions in one function propagate through the organisation.Design and prototype the human-AI interaction model — how users pose scenarios, how results are presented, and how uncertainty is communicated.
Apply by 30 Sept
Oulu, RAIDE portfolio
Healing the Planet
BackgroundElectric aviation is not simply conventional flying with a different fuel source. The operational characteristics of electric aircraft — shorter range, smaller passenger capacity, and significantly longer ground turnarounds due to charging or battery swapping — create a fundamentally different product from the jet flights passengers are used to. The booking experience, the airport journey, the wait on the ground, and the flight itself all need to be rethought for a context where a 45-minute charge stop is not a failure but a designed part of the service. Passengers arriving at a regional electric flight with jet-era expectations will be disappointed; passengers arriving with accurate expectations and a well-designed experience around the constraints may find something they actively prefer. Getting the experience design right is not a cosmetic concern — it is a core condition for regional electric aviation achieving mainstream adoption.ProblemKey questions to be answered in the project:How do different passenger personas — leisure travellers, business commuters, connecting passengers — experience and evaluate the trade-offs specific to regional electric flight, particularly around ground dwell time?What do passengers actually do, need, and feel during an extended ground turnaround, and how does this differ between a charging scenario and a battery-swap scenario?Which touchpoints in the end-to-end journey — booking, pre-departure communication, airport arrival, boarding, ground wait, in-flight, arrival — carry the greatest experience risk and the greatest design opportunity?How should the booking and pre-departure flow set accurate expectations without making the product sound unattractive compared to conventional alternatives?What physical and digital infrastructure at small regional airports would most improve the ground dwell experience, given the constraints of limited terminal space and lower passenger volumes?In this project we aim to...Produce a service blueprint covering the end-to-end regional electric flight passenger journey for at least three distinct passenger personas, with explicit side-by-side comparison of the charging-wait and battery-swap-wait scenarios.Prototype the booking and at-airport experience flows, with particular attention to expectation-setting and the design of the ground dwell period.Identify the infrastructure and service design requirements that small regional airports would need to meet in order to deliver the proposed experience.
Apply by 30 Sept
Oulu, RAIDE portfolio
Value Creators of Tomorrow
Maintenance work is often documented poorly or not at all — technicians are focused on the task, not on writing it up afterwards, and structured documentation is time-consuming to produce manually. Yet this documentation is valuable: it supports training, quality assurance, and knowledge transfer between technicians. A prior Demola team showed that feeding a 40-minute maintenance video into a large cloud-based model with a minimal prompt could produce surprisingly detailed, tool-level documentation automatically. The open question is whether this same capability can be achieved with smaller, locally runnable models — which would make the approach viable in privacy-sensitive or connectivity-constrained field settings. Key questions to be answered in the project: 1. How accurately can structured maintenance documentation (steps, tools, materials, sequence, timing) be extracted automatically from video? 2. How much prompt engineering is needed to get reliable structured output from models of different sizes? 3. At what point does a small, locally runnable model become 'good enough' for this use case compared to large cloud-based models? 4. What are the privacy implications of video-based documentation, particularly around recording workers and GDPR compliance? 5. How should the extracted documentation be validated or corrected by a human before being used for training or quality purposes?In this project we aim to... - Build a working pipeline prototype that extracts structured maintenance documentation from task videos. - Compare performance across at least two model sizes, including at least one small, locally runnable model. - Document the privacy and deployment constraints relevant to using this approach in real maintenance environments.
Apply by 30 Sept
See how Demola has helped students around the world succeed in their careers and personal lives.
Master’s Degree student in Research and Innovation in Higher Education
Excellent
20/04/2023
“I enjoy connecting with other people who are not from the same area and field, and creating new things. I think Demola is a very great platform and, since I’m interested in education, I think this is a great idea to help students and other people to learn in a different way and to be closer to the work life.”
Master’s Student in Public and Global Health
Excellent
20/04/2023
“I joined Demola for the third time already, since I enjoy how my personal skills are developing here and I love the feeling of freedom of thoughts, to be able to think, feel and express anything.”
Master’s Student in Sustainable Digitalisation
Excellent
20/04/2023
“I wanted more experience in interdisciplinary project work and real-life, tangible development of solutions with external stakeholders. I also wanted to practice what the design process is like in the real world and how to present novel ideas in an attractive, business- oriented way. And Demola delivered!”
Master’s Degree Student in Engineering and Technology
Excellent
10/06/2022
“In Demola we focused on creating solutions that can and should be applicable and should happen in real life, concrete and implementable solutions that can have an impact. Those type of solutions that go way beyond than just making a new website or a nice social media page.”
Master of Business
Excellent
17/04/2023
“If you have successfully completed the Demola project, it is proof of your passion and that your mindset is inevitably customer-oriented. Demola is definitely an experience I can recommend to all students.”
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