Research infrastructures

Area Science Park has significantly upgraded the hardware infrastructure and computing power of ORFEO, the Data Center that serves as a cornerstone of the organisation’s research and innovation ecosystem. Supported by the PNRR – Mission 4 “Education and Research”, the Data Center expansion marks a major step forward in computing performance and in the delivery of advanced storage and data management services for scientific applications in numerical simulation and artificial intelligence.   A more powerful and sustainable Data Center The €3 million investment through PNRR funds has enabled the creation of a new 125 kW server room equipped with high-efficiency cooling systems, reducing both the carbon footprint and operational costs. Computing capacity has been enhanced with new servers for simulations and predictive modelling, supported by three AI nodes, each with eight state-of-the-art GPU accelerators. These resources make it possible to train large language models, run computer vision applications, and analyse complex datasets in a fraction of the time. Internal interconnections have been upgraded with ultra-low-latency, high-speed links to ensure smooth data flow even under heavy workloads. Storage capacity has been increased by several petabytes, with the addition of an ultra-fast solid-state memory layer for “hot” datasets, further improving performance and efficiency. “ORFEO represents a strategic investment for Area Science Park, enabling the full operation of the organisation’s research and technological infrastructures,” explained President Caterina Petrillo. “It manages the entire data lifecycle from our genomics and virology research laboratories, materials microscopy, and soon, from the green energy production demonstrator. ORFEO also provides AI and HPC access and services to companies, driving digital transformation and business competitiveness in coordination with the regional data center network. To sustain excellence and the quality of our data science investments, Area Science Park has developed an advanced training programme for young researchers and technologists”.   A key infrastructure for scientific research As the digital core of Area Science Park’s research activities, ORFEO supports advanced projects in artificial intelligence, materials science, computational biology, and genomics. Thanks to its high-performance architecture, the Data Center enables researchers to run complex simulations, train large-scale machine learning models, and analyse massive amounts of scientific data in a reproducible and traceable way. The infrastructure also powers a broad research ecosystem focused on AI model interpretability and the energy sustainability of computational processes. ORFEO hosts automated pipelines integrating high-performance and cloud computing, ensuring data interoperability and faster analysis. Its evolution strengthens collaborations with universities, research institutions, and national and European infrastructures, consolidating Area Science Park’s role as a hub for computational research and digital innovation.   An ally for digital business transformation Beyond supporting scientific research, ORFEO is a strategic asset for enterprises seeking to innovate through high-performance computing and artificial intelligence. Area Science Park provides consulting services, feasibility studies, and Proof of Concept projects to facilitate the adoption of advanced digital solutions—from numerical simulation to data science—within a secure, high-performance environment.   ORFEO is Area Science Park’s high-performance computing and artificial intelligence Data Center, designed to support scientific research and industrial innovation. Established in 2020 to serve the life sciences, it now functions as a cross-sector platform integrating HPC, AI, and big data management. It enables the training of advanced models, digital twin simulations, and FAIR-compliant data repositories linked to the organisation’s experimental laboratories. The infrastructure provides services in Infrastructure, Platform, and Software as a Service (IaaS, PaaS, and SaaS) modes, with ready-to-use environments and tools for data science and HPC. The cluster delivers millions of computing hours annually, is connected to national research backbones (LightNet, GARR), and follows open standards to ensure interoperability and security. Technical management is entrusted to the Data Engineering Laboratory (LADE), which brings together expertise in AI, data engineering, and high-performance computing.

The second edition of the Master in Data Management and Curation (MDMC), organised by Area Science Park and SISSA – International School for Advanced Studies, started on 22 September. This post-graduate advanced training course provides young researchers as well as professionals with advanced skills in managing research data according to the FAIR principles (Findable, Accessible, Interoperable, Reusable). This approach has become essential to ensure the quality, integrity and reusability of scientific data and to promote a culture of open science at the international level. The programme was recently presented at CERN by Mariarita de Luca and Federica Bazzocchi from Area Science Park during the Open Science Fair 2025, held in Geneva from 15 to 17 September. On that occasion, the theme of FAIR data and the advanced skills required for their management was discussed as a key element in supporting the next generation of researchers. “Today data drive discovery, innovation and decision-making,” explain the researchers from Area Science Park. “For this reason, the ability to manage and curate them responsibly is crucial. Ours is a pioneering training programme that embraces the ‘FAIR-by-design’ paradigm, going beyond theory: instead of retrofitting datasets to FAIR criteria, MDMC students learn to integrate the FAIR principles from the earliest stages of data planning within the broader context of Open Science. This innovative approach is made possible thanks to the strong collaboration between Area Science Park and SISSA, which provides a dynamic ecosystem of research and innovation”. The second edition of the Master brings together 15 students from 7 different countries, with academic backgrounds ranging from Genetics to Electronics, Physics to Data Science, as well as Linguistics, Psychology, Economics and Mathematics. The 2025–2026 class also stands out for its diverse backgrounds: 3 students already hold a PhD, 7 have a Master’s degree and 5 a Bachelor’s degree. The programme lasts ten months and combines lectures, laboratory activities and internship periods at research centres and high-tech companies. Its aim is to train professionals capable of working as Data Stewards, Data Curators, Data Engineers and Data Managers in both scientific and industrial contexts. More specifically, the structure of the course includes eight intensive weeks of in-person lectures and hands-on exercises, followed by six months of internship in cutting-edge research laboratories or data-intensive institutions. During this period, students implement FAIR-by-design workflows and pipelines in real scientific contexts. This model provides a unique opportunity to work closely with researchers, develop tailored data management strategies and face the practical challenges of semantic interoperability, metadata standards and sustainable infrastructures. By training versatile, practice-oriented data professionals, the MDMC contributes to shaping a new generation of researchers capable of transforming data from a mere research product into a strategic asset, crucial for both academic excellence and data-driven innovation. For further details, see the course’s scientific programme. Watch the video featuring testimonials from students of the first 2024–25 edition.

SECOND CALL: Applications for the course are open again, thanks to the introduction of additional scholarships and new “Auditor” participation option. — Advanced, hands-on training for the next generation of data professionals, delivered in the heart of Trieste’s renowned scientific ecosystem. In today’s data-driven world, the ability to manage, curate, and leverage data effectively is paramount. Both scientific research and industry increasingly demand professionals skilled in making data Findable, Accessible, Interoperable, and Reusable (FAIR). Furthermore, in today’s AI-driven landscape, mastering data management is absolutely critical to safeguarding the integrity and security of the algorithms we increasingly rely on. The one-year professional course “Master in Data Management and Curation (MDMC)”, a unique joint initiative by Area Science Park and SISSA, is designed to equip you with the advanced, practical skills needed to excel in this critical field. Why Choosing  MDMC? Prestigious partnership: Learn from two leading institutions: Area Science Park, a national public research organisation, which has always been a link between research, innovation and industry, and SISSA, one of the six Italian school of excellence, which is a scientific center of advanced research in mathematics, physics and neuroscience within the national and international academic scene. Both share the scientific objective of doing frontier research in the field of Artificial Intelligence. This unique collaboration offers an unparalleled learning environment. Specialized FAIR & Open Science focus: Gain in-depth expertise in FAIR principles and Open Science methodologies, skills highly sought after by research institutions and funding bodies across Europe. Unique hands-on approach: Go beyond theory with our innovative “FAIR-by-design” methodology. Apply your learning during a six months extensive practical internship within real, cutting-edge research laboratories and companies. Targeted career outcomes: Prepare for in-demand roles like Data Steward, Data Curator, Data Engineer and Research Data Manager, equipped with the practical experience needed in academia, research infrastructures and private data-intensive organizations. MDMC Objectives The Master program is designed to provide with both the theoretical foundation and the practical, hands-on skills essential for managing the entire research data lifecycle effectively and responsibly. Upon successful completion of the Master in Data Management and Curation, you will be able to: Master FAIR Principles & Open Science: Deeply understand and advocate for the principles of Findable, Accessible, Interoperable, and Reusable (FAIR) data within the broader context of Open Science methodologies and European initiatives like EOSC (European Open Science Cloud), European Commission funders and others.    Implement FAIR-by-Design Workflows: Design, implement, and manage practical “FAIR-by-design” data workflows and pipelines  directly within research environments, ensuring data is managed correctly from collection to publication and beyond. Develop Comprehensive Data Management Plans (DMPs): Create, evaluate, and execute robust Data Management Plans tailored to specific research projects, addressing funder requirements and best practices.    Manage Metadata Effectively: Define, create, enrich, and utilize rich metadata using appropriate standards, schemas, ontologies, and vocabularies to ensure data discoverability and interoperability.    Utilize Data Management Tools & Technologies: Gain practical experience with essential tools, software (including Python for data management ), database systems, data formats, and potentially cloud environments for data acquisition, curation, analysis, and storage.    Curate and Preserve Research Data: Apply best practices for data curation, including data quality assessment , documentation , storage , and long-term preservation strategies using appropriate repositories.    Navigate Legal & Ethical Frameworks: Understand and apply principles related to data protection (e.g., GDPR ), intellectual property, data licensing , and research ethics, particularly when handling sensitive data.    Understand AI Fundamentals and Applications: Grasp the core concepts of Artificial Intelligence and explore its practical applications in various scientific domains, bridging the gap between AI theory and real-world scientific challenges. Perform Foundational Data Analysis: Apply introductory statistical analysis and machine learning concepts to explore and understand research data.    Operate as a Data Steward: Be prepared to act as a skilled Data Steward, Data Engineer or Research Data Manager within research institutions or other data-intensive organizations. This professional course provides the opportunity to acquire robust technical competencies (e.g., in data handling, metadata management, tool usage) that can be applied at various levels, allowing you to tailor your positioning within the Data Steward role based on your career aspirations and the specific needs of the organization. Duration and Modality The MDMC is a full-time 10 months program, which consists of 1500 hours of training activities, corresponding to 60 ECTS credits. Total Duration: 10 months, from September 15, 2025 to June 30, 2026 Teaching Language: English Teaching Mode: In-person, with some remote sessions during the internship period Location of in-presence lectures: Trieste – Area Science Park & SISSA Admission Requirements (Academic Year 2025-2026) Admission to the Master in Data Management and Curation – MDMC – for the Academic Year 2025-2026 requires candidates to hold a Bachelor’s degree (Laurea Triennale) or a Master’s degree (Laurea Magistrale/Specialistica), or an equivalent university degree (e.g., pre-reform Italian Diploma di Laurea). In addition to the degree qualification, candidates must meet the following minimum requirements by the start date of the lessons to effectively follow the program: English language: a good proficiency in English is required (CEFR B2 level or higher), as all lectures and teaching activities will be conducted exclusively in English. Python programming: basic Python programming skills are required, as detailed in the Annex 1. Mathematical skills: minimum mathematical knowledge equivalent to that acquired through university-level Calculus 1 and 2 courses (or equivalent). Statistical skills: basic knowledge of statistics, including elements of probability theory, hypothesis testing techniques, understanding of Bayes’ theorem, and statistical model comparison. Technical equipment: availability and ability to use a personal computer equipped with a functioning Linux operating environment. Applications for the Academic Year 2025-2026 must be completed and submitted exclusively through the dedicated online platform, accessible at the following link: PICA – Master in Data Management and Curation: MDMC. Application Call 2025 – 2026 THE APPLICATION WILL BE OPEN FROM JULY 24TH TO AUGUST 20TH AT 13:00. The online procedure requires uploading the following mandatory documents: Letter of motivation: a document outlining the candidate’s reasons for interest in the MDMC Master and their professional goals (150 – 1500 characters). Identity Document: a copy (front and back) of a valid identity document (ID card or passport). Curriculum Vitae: an updated CV detailing the candidate’s educational background and any professional experience. Participants, fees and fellowships In this second call for the 2025–2026 edition of MDMC, both regular participants and auditors are eligible to apply. Participants For the Academic Year 2025-2026, the Master in Data Management and Curation (MDMC) will admit a maximum of 15 participants.  For participants, the standard tuition fee is € 4,500.00, which includes: attendance to all in-person lectures held in Trieste; participation in a laboratory or internship hosted by one of MDMC’s partner institutions or companies. The participants’ selection process will be based on the evaluation of qualifications (CV, academic background and motivation letter) submitted with the application. The selection committee may also invite candidates for an individual online interview to further assess their preparation, skills, and motivation. At the end of the process, a final ranking of admitted candidates will be established.  External supporters will participate in the participants’ selection, based on the position in this final ranking, the following financial aid packages will be available: Two grants of €4,500 each to cover the full tuition fee for the MDMC program, one of which will be awarded to a candidate holding a Master’s degree (laurea magistrale or specialistica) in Computer Engineering with a minimum grade of 102–103 out of 110; One grant of €4,500 to cover the MDMC tuition fee, in addition to a €3,000 advanced training scholarship; Two grants of €7,500 each, covering the €4,500 tuition fee and including an advanced training scholarship of €3,000, to be primarily awarded to students from institutions within the EFC network, and secondarily to students from national and international universities. Auditors Participation as an auditor is allowed for up to 5 individuals, or more provided that the total number of students (regular participants and auditors) does not exceed 20. The registration fee for auditors is € 2,500, which includes access only to the in-person lectures in Trieste, offered from mid-September to mid-December 2025. Auditorswill not take part in the internship or in the final thesis project. If the total number of students (regular participants and auditors) does not exceed 20, auditors will not be subject to selection. Those who attend at least 70% of the scheduled lectures will receive a certificate of participation listing the courses attended. Fellowships are not available for auditor participants. Ready to Shape the Future of Data? << Apply now!>>   For all information on the program and course content, application procedure, selection, financial aid and fees: download download the official Call (available only in Italian), or the Scientific Program. For further information you can visit the page on the SISSA website, or contact us sending an email to MDMC   The course is part of the NFFA-DI project, which has received financial support from Italy’s National Recovery and Resilience Plan (PNRR), Mission 4 “Education and Research” – Component 2 “From Research to Business” – Investment Line 3.1 “Fund for the implementation of an integrated system of research and innovation infrastructures”, funded by the European Union – NextGenerationEU.