Euregio-Jungforscher:innenpreis

2026 werden bereits zum 15. Mal Nachwuchsforscher:innen aus der Euregio Tirol-Südtirol-Trentino eingeladen, ihre Forschungsarbeiten einzureichen.

Die Verleihung des Euregio-Jungforscher:innenpreises 2025 beim European Forum Alpbach: (v.l.) LH Arno Kompatscher (Südtirol), LH Anton Mattle (Tirol), Präsidentin Ulrike Tappeiner (Jurypräsident und Präsidentin Freie Universität Bozen), Präsidentin Barbara Thaler (Wirtschaftskammer Tirol), Julia Hofmann (3. Platz), Eva Casotti (1. Platz), Elena Fogazzi (2. Platz), Präsident Andrea De Zordo (Handelskammer Trient), Landesrat Simone Marchiori (Trentino) und Präsident Michl Ebner (Handelskammer Bozen). © Land Tirolo/Sedlak

Schließen

Anlässlich der Euregio Days 2026 in Alpbach, die sich dem Thema „Starke Regionen. Starkes Europa. gemeinsam!" widmen, können Nachwuchsforscher:innen unter 35 ihre Arbeiten einreichen, vorstellen und sich mit renommierten Wissenschaftler:innen und politischen Verantwortungsträger:innen austauschen.

Zum Jungforscher:innenpreis 2026 sind junge Forschende aus der gesamten Euregio zugelassen. Die Finalist:innen können in Alpbach ihre Forschungsarbeiten vorstellen, wo am Abend des 29. August 2026 auch die Preisverleihung stattfindet. Die zwei Förderpreise stammen auch heuer wieder von den Handels- und Wirtschaftskammern der drei Euregio-Länder.

In diesem Jahr präsentieren die drei besten Forschenden jeder Kategorie ihre Forschungsarbeiten einer hochkarätig besetzten Jury in Alpbach, wobei die Bewertung getrennt nach Kategorien erfolgt.

Kategorie: Wirtschaft, Sozialwissenschaften, Rechtswissenschaft, Bildung und Geisteswissenschaften
Kategorie: Technische Wissenschaften, Naturwissenschaften und Medizin

Finalist:innen 2026

Kategorie 1: Wirtschaft, Sozialwissenschaften, Rechtswissenschaft, Bildung und Geisteswissenschaften

Philipp Jaufenthaler

Strengthening Regions in a Volatile World: Experimental Evidence on the Localness Effects of Family Firm Status

In a volatile world, local identity is a key driver of resilience. This study investigates family firm branding as a strategic tool for the Euregio’s competitiveness. Adopting an interdisciplinary framework bridging consumer psychology and strategic management, five experimental studies (1,654 participants) examine how perceived family firm status influences dimensions of localness: geographical reach, iconness, national origin, and domestic production. Findings show that family firm status significantly enhances purchase intention, primarily driven by “Local Iconness”—the perceived cultural embeddedness of a brand. For the Euregio, where family firms form the economic backbone, these results offer an efficient blueprint for leveraging their local strengths while remaining competitive in global markets, directly contributing to the building of resilient and strong regions.

Anna Bertani

Infodemics and Institutional Resilience: Lessons for European Cross-Border Regions

The COVID-19 pandemic has been accompanied by an “infodemic” of misinformation that undermines effective public responses. This study investigates how socioeconomic and institutional factors influence vulnerability to misinformation across 37 OECD countries using social media data and advanced computational methods. We show that infodemic dynamics are not uniform but follow distinct trajectories shaped by polarization, institutional quality, and media diversity. Diverse news ecosystems and strong institutions emerge as key protective factors. These results have direct implications for cross-border regions such as the Euregio Tyrol–South Tyrol–Trentino, where linguistic diversity, fragmented media systems, and multi-level governance create unique challenges. The study highlights the need for coordinated regional strategies to strengthen information resilience and support European cohesion.

Ece Naz Tatar

Tokenising Regional Capital Flows: A DLT Pilot Regime and MiCA-Compliant Security Token Model for Cross-Border Investment in the Euregio Tyrol-South Tyrol-Trentino

The European Region Tyrol-South Tyrol-Trentino, formally established as an EGTC, embodies the European Forum Alpbach 2026 theme “Strong Regions. Strong Europe. Together!” by promoting cross-border cooperation. Yet small investors and SMEs face insurmountable barriers when financing neighbouring projects such as hydroelectric plants, agricultural cooperatives, or start-ups due to differing legal frameworks, tax mismatches and administrative hurdles between Austria and Italy (Fit4Co CBO, 2025; EIB, 2025/26). This paper proposes a DLT Pilot Regime and MiCA-compliant security token model that enables fractional ownership of real regional assets through smart contracts. The original Euregio Token prototype creates a borderless, MiFID II-exempt investment channel, automates dividends, tax withholding and KYC/AML, and turns Euregio citizens and SMEs into active co-investors. The model directly operationalises the “Together!” spirit and serves as a blueprint for other European border regions.

Kategorie 2:Technische Wissenschaften, Naturwissenschaften und Medizin

Moritz Ploner

Wearable Sweat Cytokine Sensing for Decentralized Health Monitoring

Access to diagnostic services remains challenging, particularly in remote Alpine areas, where repeated access to conventional laboratory-based blood analysis may be limited. In this setting, wearable biochemical sensing offers a promising route toward decentralized health monitoring. Against this background, the project develops a wearable platform for the non-invasive detection of inflammatory biomarkers in sweat, focusing on the cytokines interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), two key indicators of immune activity and chronic inflammation. By integrating flexible electrochemical sensors, microfluidics, and machine-learning-based signal analysis, the platform enables sensitive, multiplexed monitoring in a wearable format. This technology could support the development of diagnostic systems for real-time health monitoring and enable future applications in telemedicine, earlier disease detection, broader access to diagnostics, and more resilient healthcare systems.

Alexander Sietmann

Autocatalytic degradation of the extremely potent greenhouse gas SF6 in basic alcoholic solution

Sulfur hexafluoride (SF6) is a persistent, highly potent greenhouse gas that is accumulating in the atmosphere at an increasing rate, exacerbating climate change. Whereas current degradation methods rely on forcing conditions to dissociate the inert molecule and additionally require post-treatment with basic solution to obtain harmless products, we show that SF6 is mineralized in a single step at ambient temperature using potassium hydroxide in water/isopropyl alcohol mixtures under UV irradiation. The reaction proceeds via an autocatalytic mechanism, where in situ-generated acetone acts as a photosensitizer, leading to the selective formation of potassium sulfite and fluoride salts. Compared to existing methods, this approach eliminates the need for extreme temperatures, hazardous catalysts, or post-treatment, providing a scalable and easy-to-apply strategy for SF6 degradation.

Margherita Mele

From Complexity to Insight: Learning from Simplified Representations

The growing abundance of data and the intrinsic complexity of natural and artificial systems pose a central challenge to modern research: how to extract meaningful information without being overwhelmed by detail. This project addresses that challenge by developing a theoretical framework, grounded in statistical physics and information theory, to identify simplified yet informative representations of complex systems. It enables the reduction of high-dimensional descriptions while preserving the collective properties that govern system behaviour. The approach has been applied to two deeply related domains: proteins, where function arises from the exploration of conformational space, and artificial neural networks, where learning emerges from the structure of parameter space. The results open new perspectives in disease understanding, drug design, and the development of more reliable and transparent AI systems.