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Tag: data science

EuMINe COST Action Third General Meeting – 7-10 July 2026 (Cluj-Napoca, Romania)

πŸ“ Cluj-Napoca, Romania
πŸ“… 7-10 July 2026

The EuMINe COST Action Third General Meeting will be held from July 7 to 10, 2025, in Cluj-Napoca, Romania. This event is a key gathering within the European Materials Informatics Network (EuMINe), an innovative initiative dedicated to advancing materials informatics through digital, data-driven technologies, and artificial intelligence. EuMINe aims to foster an interdisciplinary and intersectoral community focused on the development and engineering of advanced materials by promoting harmonized approaches and shared resources across Europe.


πŸ‘‰ For more information visit the Meeting Website: https://www.itim-cj.ro/eumine3rd/

πŸ” Meeting Focus: Working Group Highlights

The meeting will serve as a platform to promote collaborative research, knowledge exchange, and strategic discussions among researchers, practitioners, policymakers, and industry stakeholders. Participants will explore the progress and future vision of EuMINe’s five working groups:

  • WG1: Shared Policies, Datasets and Standardization
  • WG2: Cooperative Development of Materials Informatics Approaches
  • WG3: Training and Capacity Building
  • WG4: Connecting R&D Activities with End Users and Stakeholders
  • WG5: Dissemination and Communication

πŸ’» EuMINe DataBridge Hackathon 2026

We are pleased to announce the EuMINe DataBridge Hackathon 2026, an initiative dedicated to advancing data-driven approaches in materials science through collaborative and interdisciplinary research.

The EuMINe General Meeting will host Stage 2 of the EuMINe DataBridge Hackathon 2026. Finalist teams will present their models in person in Cluj-Napoca and take part in a collaborative final session, with full reimbursement of travel and living expenses.

Full details, including participation information and program structure on the Hackathon website:

https://www.eumine-cost.eu/eumine-databridge-hackathon-2026/

Stay tuned for updates!

πŸ“Œ Programme

Download the complete programme here!

πŸ“ Application Details

πŸ—“οΈ Extended Deadline: 31 May 2026 10 June 2026
πŸ‘‰ Apply now

πŸ’Ά Financial Support

The EUMINE Cost Action is pleased to provide the opportunity for reimbursement to participants (travel expenses coverage and daily allowance), supporting their attendance at the meeting:

  • Invited speakers, Management Committee (MC) members and EuMINe Core Group (CG) members
  • Working Group (WG) and other participants will be selected for reimbursement upon the following criteria:
    • Active participation in the meeting by submitting an abstract. The presenting author will only be considered for reimbursement.
    • Gender, age, and geographic inclusivity (ITC/NNC balance)
    • Potential contribution to the Working Groups

πŸ“… Important Dates

  • Application Deadline: 31 May 2026
  • Notification of Acceptance: 10 June 2026

πŸ“ Practical Information

Venue

Red Amphitheater, USAMV
Calea Mănăștur 7
400394 Cluj-Napoca, Romania

ML4MatSci: Hands-on Machine Learning for Research in Materials Sciences – 2nd PhD Summer School

πŸ“ Sarajevo, Bosnia and Herzegovina
πŸ“… 10-12 June 2026

The ML4MatSci PhD School aims to equip current and prospective PhD students with a solid foundation in machine learning (ML) methods, demonstrated through real-world research led by scientists actively applying ML in their own work.

Our goal is to empower and inspire PhD students to confidently integrate ML into their research, fostering creativity, critical thinking, and innovation in applying data-driven approaches to materials science and related fields.

πŸ” Why attend

The ML4MatSci PhD School offers a unique opportunity to:

  • Discover how cutting-edge AI is transforming materials science research
  • Gain hands-on experience with modern tools for modeling, simulation, and characterization
  • Present your research and receive expert feedback
  • Network with leading researchers and peers
  • Join a growing interdisciplinary community at the intersection of AI and materials science

πŸ‘₯ Target Audience

  • PhD students and postdoctoral researchers in Materials science, Physics, Chemistry, Computer science
  • Aspiring PhD students interested in AI-driven research

πŸ“š Prerequisites

  • Basic programming knowledge (Python preferred)
  • Fundamentals of ML and AI
  • Understanding of datasets and evaluation metrics
  • Enrollment in (or preparation for) a PhD program in a relevant field

πŸ”¬ Scientific Focus Areas

  • Generative AI for Materials Science
  • Agentic AI & Multi-Agent Systems
  • Digital Twins of Materials and Processes
  • Large Language Models (LLMs)
  • Graph Neural Networks & Physics-informed Neural Networks
  • Foundation models for materials science
  • Explainable AI (XAI) and multi-modal learning
  • Tools & Languages: Python, PyTorch, TensorFlow, JAX, Scikit-learn

πŸ§ͺ Teaching Format

The school runs over three intensive days, combining theory and practice:

  • πŸ“š Lectures – Advanced AI topics delivered by leading experts
  • πŸ’» Hands-on Sessions – Practical workshops on ML tools and methods
  • 🏭 Industrial Session – Real-world ML applications in industry
  • 🎀 Poster Session – Present and discuss your research
  • ⚑ Elevator Pitches – Short, impactful research presentations

πŸ‘©β€πŸ« Lecturers

  • Jacob Goldberger – Bar-Ilan University (Israel)
  • Keith Butler – University College London (UK)
  • Salim Belouettar – Luxembourg Institute of Science and Technology (Luxembourg)
  • PatrΓ­cia Ramos – Polytechnic of Porto / INESC TEC (Portugal)
  • Michael Moeckel – Technische Hochschule Aschaffenburg (Germany)
  • Amila Akagic – University of Sarajevo (Bosnia and Herzegovina)
  • Amra Hasecic – University of Sarajevo (Bosnia and Herzegovina)

πŸ“Œ Programme

πŸ—“οΈ Day 1 – Wednesday, June 10, 2026

Venue: Faculty of Electrical Engineering, Room A4

Time Session Speaker/Lead Format
08:00 – 08:30 Registration Organizers Welcome
08:30 – 09:00 Welcome addresses and programme overview Organizers Welcome
09:00 – 10:00 Materials Informatics with Graph Neural Networks: From Handcrafted Features to Deep Representations Amila AkagiΔ‡ Lecture
10:00 – 11:00 1st Hands-on Session β€” Hands-on
11:00 – 11:30 Coffee Break β€” Break
11:30 – 12:30 Informed Machine Learning for Physical Systems: From Graph Neural Networks to Physics-Informed Neural Networks Michael Moeckel Lecture
12:30 – 13:30 2nd Hands-on Session β€” Hands-on
13:30 – 15:00 Lunch β€” Break
15:00 – 15:30 Artificial Intelligence and HPC: Current Research Landscape and Opportunities Dr. Lemana SpahiΔ‡ Lecture
15:30 – 16:30 Physics-Informed Machine Learning for Computational Mechanics: Bridging Data and Physical Laws Salim Belouettar Lecture
16:30 – 17:30 3rd Hands-on Session β€” Hands-on
17:30 – 18:00 Coffee Break β€” Break
18:00 – 19:00 Elevator poster pitches Participants Presentations
19:00 – 20:00 Poster Session I Participants Poster session
20:00 – 20:45 Reception β€” Reception

πŸ—“οΈ Day 2 – Thursday, June 11, 2026

Venue: Faculty of Electrical Engineering, Room A4

Time Session Speaker/Lead Format
09:00 – 10:00 Confidence Calibration Jacob Goldberger Lecture
10:00 – 11:00 4th Hands-on Session β€” Hands-on
11:00 – 11:30 Coffee Break β€” Break
11:30 – 12:30 Property-Guided Generative Models for Molecular Materials Discovery Patricia Ramos Lecture
12:30 – 13:30 5th Hands-on Session β€” Hands-on
13:30 – 15:00 Lunch β€” Break
15:00 – 16:00 Elevator poster pitches Participants Presentations
16:00 – 17:00 Poster Session II Participants Poster session
17:00 – 18:00 Walking Tour Local organizers Social programme

πŸ—“οΈ Day 3 – Friday, June 12, 2026

Venue: Faculty of Mechanical Engineering, Room β€œSvedski amfiteatar 1”

Time Session Speaker/Lead Format
09:00 – 10:00 From Simulation Data to Explainable Predictions: Deep Learning and Engineering Applications Amra Hasecic Lecture
10:00 – 11:00 6th Hands-on Session on LLMs β€” Hands-on
11:00 – 11:30 Coffee Break β€” Break
11:30 – 12:30 The Nuts and Bolts of Graph Neural Networks for Chemistry and Materials Science Keith Butler Lecture
12:30 – 13:30 7th Hands-on Session β€” Hands-on
13:30 – 15:00 Lunch β€” Break
15:00 – 16:00 Fundraising for DeepTech: Translating Frontier Science into Investable Companies Andrea Jagodic Lecture
16:00 – 17:00 8th Hands-on Session β€” Hands-on
17:00 Closing and departure from Sarajevo Organizers Closing

πŸ“ Application Details

πŸ—“οΈ Deadline: 10 April 2026
πŸ‘‰ Apply now

πŸ“„ Required Documents

Applicants must submit:

  • Short CV (1 page)
  • Motivation letter (Β½ page)
  • Poster title and abstract (ΒΌ page)
  • Travel cost estimate (in Eur)
  • Statement on participation without EU funding

πŸ’Ά Financial Support

The EuMINe COST Action is pleased to offer reimbursement for up to 20 participants, covering travel expenses and daily allowances. Participants will be selected based on:

  • Interest in the school by submitting the CV, a motivation letter and a poster abstract 
  • Gender and age balance
  • Geographic inclusivity, with preference for Inclusiveness Target Countries (ITCs) and Near Neighbour Countries (NNCs)

πŸ“… Important Dates

  • Application Deadline: 10 April 2026
  • Notification of Acceptance: 16 April 2026

πŸ§‘β€πŸ’Ό Organizers

  • Michael Moeckel – Technische Hochschule Aschaffenburg (Germany)
  • Amila Akagic – University of Sarajevo (Bosnia and Herzegovina)
  • Amra Hasecic – University of Sarajevo (Bosnia and Herzegovina)
  • Francesco Mercuri – National Research Council (Italy)

πŸ“ Practical Information

Location: Sarajevo, Bosnia and Herzegovina

Venue

Faculty of Electrical Engineering
University of Sarajevo
Kampus Univerziteta
71000 Sarajevo

πŸ“§ Contact:
Amila Akagic β€” aakagic@etf.unsa.ba

AI & Material Science – 24-26 September 2025 (Ljubljana, Slovenia)

We are pleased to invite you to submit an abstract to the AI for Materials track, taking place in Ljubljana fromΒ September 24 to 26, 2025. The event is co-organized by the β€œEuropean Materials Informatics Network” and the β€œData-driven Applications towards the Engineering of functional Materials: an Open Network”, under the auspices of the European Cooperation in Science and Technology funding organisation.

Our event aims to bring together scientists, innovators, start-ups, and industry leaders to explore the state of the art and latest breakthroughs in artificial intelligence for materials discovery. Discussions will focus on identifying current limitations, overcoming bottlenecks, and fostering an open, synergic ecosystem for AI-driven materials research in Europe – where academia, large enterprises, start-ups, and scale-ups thrive together.

The EUMINE COST Action CA22143 and DAEMON COST Action CA22154 act as a co-organizer of the event. COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation.

πŸ“ Important dates

  • 15. 7. 2025 – Paper/abstract submission deadline
  • 21. 7. 2025 – Notification of acceptance
  • 25. 7. 2025 – Camera-ready version and Author registration deadline

πŸ‘‰ Submission link

Conference Topics:

  • Materials discovery: automated computational and experimental workflows
  • Materials modeling: fast and accurate simulations
  • Retrosynthesis discovery: LLMs and agentic-AI
  • Process-Structure-Property relationship discovery
  • Materials informatics: from material discovery to market

Submission Guidelines
Abstracts must be submitted using the Springer LNCS template. Both LaTeX and Word versions are available.
Abstracts will be included in the conference proceedings
Length: 1–2 pages (including references), formatted in LNCS style.
All submissions should include: Title, Authors, Affiliations, Keywords, Main text, and References.
Title: Concise and informative.
Authors and Affiliations: Full names and institutional affiliations.
Keywords: 3–5 relevant terms (e.g., deep learning, materials discovery)

Main Text:

  • Intro/Motivation: Brief context on the materials challenge.
  • Method: Brief description of the AI technique(s) adopted.
  • Results: Key findings or objectives, ideall with one figureConclusion/Future Work: Final remarks or outlook.

Program Chairs

  • Francesco Mercuri (CNR Bologna)
  • Kevin Rossi (TU Delft)

For more information visit the conference website

AI & Material Science