Non-academic placement and capacity building | July 3
Non-academic placement and capacity building | benefits for career and MSCA PF application
July 3, 2026 | 9 AM (CEST) | Online via Zoom
Meetup for those interested in non-academic experience and positioning your research career. We will share information, ideas, and experiences about the benefits of non-academic placement and how non-academic activity is beneficial for researchers’ capacity building.
Advantages include extra months and funding, a higher proposal acceptance rate, a clearer demonstration that the researcher is committed to maximise expected outcomes and impacts, and a realistic exploitation plan.
The meetup is intended to share information briefly and answer questions that you bring.
The introduction is given by Dr. Syväjärvi who has more than 20 years of experience from international technology transfer, start-up creation and research-to-business activities. This experience forms the basis for his SME, Alminica AB, which contributes to European research projects with transfer of knowledge for impact and exploitation from research and innovation towards business and sustainability. Recent examples include the EU FET Open project SiComb (2020–2024) and the EIC Pathfinder project rePowerSiC (2024–2028). He has recently been accepted as a mentor in European Innovation Council (EIC) 2026 initiatives, including the EIC Tech to Market Programme and the EIC Women Leadership Programme. These activities involve supporting researchers and innovators in areas such as value proposition development, early-stage commercial thinking, leadership development, and strategic reflection on future opportunities arising from research and innovation.
From Impact to Exploitation – Summer 2026
Two options will be available. Dates to be announced. Contact us with your interest.
Short course
From impact to Exploitation: Basics and Perspectives for Exploitation Pathways
Summer course
From impact to Exploitation: Exploitation Pathways and Research Case Development
More information: From Impact to Exploitation
Machine Learning in Deeptech | Webinar Jun 23, 2026
Project webinar June 23, 2026 10 AM (CEST)
Machine Learning in Deeptech: Machine Learning Before Machine Learning
Abstract:
Machine learning depends on data. However, many deeptech and EIC Pathfinder projects involve early-stage process development with limited data and few experiments or samples.
Machine learning and AI are useful for development, but research activities are only one link in a larger chain. Optimizing a single process step may miss strategically important data connected to manufacturing, sustainability, traceability, and future exploitation. What data should be considered before large datasets are available? The webinar aims to open discussion and exchange around “machine learning before machine learning” and how early-stage deeptech projects can prepare for machine learning, AI, and data-driven value creation. As a case study, experiences from CS-PVT pilot activities in rePowerSiC will be presented.
More details:
Machine learning depends on data. However, many deeptech and EIC Pathfinder projects are still in early-stage development, where data is limited, experiments are few, and processes are still being developed.
Machine learning and AI are often proposed for developing a specific activity. However, the activity is one link in a larger (value) chain. Optimizing only a single process step may overlook strategically important data connected to the broader value chain. This is especially important in Pathfinder projects, where research is expected to progress towards impact and exploitation.
What data should be created already now, before large datasets are available?
This challenge exists in rePowerSiC and many other deeptech projects. The CS-PVT process used to fabricate SiC base layers (epiwafers) for high-power laser conversion may eventually reach high technical performance. However, technical performance alone is not sufficient. A real challenge is that once there is a commercial market, PVT manufacturing (like China) will learn about CS-PVT and rapidly scale epiwafer production capabilities.
Competitiveness may therefore depend not only on process performance itself, but also on data-driven added value.
Machine learning should extend beyond optimisation of individual process steps towards value-chain optimisation, predictive maintenance across manufacturing systems, process intelligence, traceability, sustainability positioning, and other aspects that emerge across the chain rather than within a single technology step.
The webinar discusses how deeptech projects can think about:
- machine learning with limited datasets,
- identifying strategically important data early,
- linking technical development to future exploitation,
- integrating sustainability and value-chain perspectives,
- and building foundations for post-project effect and long-term impact.
We will present experiences from our own pilot in CS-PVT.
Organized by the EIC Pathfinder project rePowerSiC.
From India and will apply for MSCA PF 2026?
Are you from India and applying for the MSCA Postdoctoral Fellowship call 2026? Active in space, innovation, emerging technologies or green transition?
You can start planning for next step after the fellowship already now. India will most likely become an associated country to Horizon Europe — which means funding calls you can apply for. If you position yourself during your fellowship, you can be part of a consortium in the FP10 programme. We have experience in how to position for being part of consortium.
We have a particular focus on India, and there is a recently announced Joint Action Plan 2026-2030 between India and Sweden covering the areas space, innovation, emerging technologies or green transition which are very relevant in our activity already.
Contact us to discuss.
Introductory course – July 2, 2026 | Data-driven Value Creation for Impact and Exploitation
Introductory Course – Online via Zoom | July 2 | 10-12 AM (CEST). Those interested in next step can develop their own case (individual course, contact us).
This is for researchers who want to
- position their research with impact and exploitation
- understand how shared data creates advantages for research and career
The content is described in main page here.
The purpose of the introductory is to give an insight and understanding. From that you can decide to take full training to develop your own case by the individual training with presentation at a final workshop.
Course fee: 250 EUR. Submit the registration form to the email address given in the form.
Ways to Find an MSCA Host — Recommendations | June 9
An open meeting with recommendations and experiences of how to find a host for MSCA Postdoctoral Fellowship Application.
