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Driving Materials Innovation with Cutting-Edge Digital Platforms, Tools, and Algorithms – 19-20 June 2025 (Athens, Greece)

This training school aims to equip scientists with the skills to utilize software tools (Isalos Analytics Platform, Asclepios KNIME nodes) and platforms (Enalos Cloud Platform, Eos Cloud Platform) for integrating design of experiments, machine learning, and multiscale simulations in the development of advanced materials and drug discovery.

🔍 Key Scientific Topics

  • Design of Experiments for Materials R&D
  • Machine Learning Applications in Materials and Drug Discovery
  • Multiscale Simulations: Atomistic to Continuum
  • Digital Platforms for Data Analytics and Modeling:
    • Isalos Analytics Platform
    • Asclepios KNIME Nodes
    • Enalos Cloud Platform
    • Eos Cloud Platform

📝 Registration & Abstract Submission

Application

🗓️ Application Deadline: 5 June 2025
👉 Apply here

Financial Support

The EuMINe COST Action is pleased to offer reimbursement for up to 14 participants, covering travel expenses and daily allowances. Participants will be selected based on:

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

📅 Important Dates

  • Application Deadline: 5 June 2025
  • Notification of Acceptance: 10 June 2025

📅 Preliminary Programme

Day 1 – 19 June 2025

10:00 – 10:30
Registration & Networking

10:30 – 11:15
Accelerating Materials Informatics using Isalos Analytics Platform
[https://isalos.novamechanics.com/]

11:15 – 11:30
Coffee Break

11:30 – 13:30
Hands-on Session on Isalos Analytics Platform – Part I
Speakers: Antreas Afantitis, Dimitra Danai Varsou, Dimitrios Mintis

13:30 – 14:30
Break

14:30 – 15:15
Multiscale Hierarchical Modeling Frameworks for Complex Chemical Systems & Computational Methods for Penetrant Sorption and Diffusion
Speaker: Niki Vergadou

15:15 – 15:30
Coffee Break

15:30 – 16:15
Enhancing Drug Discovery with Asclepios KNIME Nodes
Speaker: Kostantinos Papavasileiou

16:15 – 16:30
Coffee Break

16:30 – 17:30
EosCloud: A Platform for Sustainable and Safe Chemical Innovation
Speaker: Anastasios Papadiamantis

Day 2 – 20 June 2025

10:00 – 10:30
Registration & Networking

10:30 – 12:30
Hands-on Session on Isalos Analytics Platform – Part II
Speakers: Dimitra Danai Varsou, Dimitrios Mintis

12:30 – 12:45
Coffee Break

12:45 – 13:30
AI-supported Materials Failure Management
Speaker: Nikolaos E. Melanitis

13:30 – 14:30
Lunch Break

14:30 – 15:15
Materials Informatics Powered by Enalos Cloud Platform Tools
Speaker: Panagiotis Kolokathis

15:15 – 15:30
Coffee Break

15:30 – 16:15
Advances in Methodologies and Algorithms for Atomistic and Coarse-Grained Simulations
Speaker: Gregory Megariotis

16:15 – 16:30
Coffee Break

16:30 – 17:30
Advanced Composite Materials and Nanotechnology for High-Performance Application
Speaker: Costas Charitidis

👨‍🏫 Lecturers and Trainers

  • Dr. Antreas Afantitis (NovaMechanics Ltd, Cyprus)
  • Prof. Costas Charitidis (NTUA, Greece)
  • Prof. Nikolaos E. Melanitis (Hellenic Naval Academy, Greece)
  • Dr. Niki Vergadou (NCSR Demokritos, Greece)
  • Dr. Grigorios Megariotis (NTUA, Greece)
  • Dr. Dimitra Danai Varsou (NovaMechanics MIKE, Greece)
  • Dr. Dimitrios Mintis (NovaMechanics Ltd, Cyprus)
  • Dr. Konstantinos Papavasileiou (NovaMechanics MIKE, Greece)
  • Dr. Anastasios Papadiamantis (Entelos Institute, Cyprus)
  • Dr. Panagiotis Kolokathis (NovaMechanics MIKE, Greece)

🏨 Venue & Accommodation

Hotel Alex, Castella, Piraeus (https://santikoscollection.com/hotels/the-alex)

📋 Committees

Organizers:

  • Dr. Antreas Afantitis (NovaMechanics Ltd, Cyprus)
  • Dr. Andreas Tsoumanis (NovaMechanics Ltd, Cyprus)
  • Dr. Francesco Mercuri (CNR, Italy)
  • Dr. Andrea Lorenzoni (CNR, Italy)

Selection Committee:

  • Dr. Antreas Afantitis
  • Dr. Konstantinos Papavasileiou
  • Dr. Panagiotis Kolokathis

Local Organization & Management:

  • Dr. Antreas Afantitis
  • Dr. Dimitra-Danai Varsou

✉️ Contact

For questions or information, please reach out to: info@novamechanics.com

13th Venice Training School: Innovating with Purpose: A Hands-on Journey into Functional, Safe and Sustainable Advanced Materials – 9-13 June 2025 (Venice, Italy)

This edition is dedicated to advancing knowledge and practice in Safe-and-Sustainable-by-Design (SSbD) for advanced materials. The school brings together experts, researchers, and industry professionals to explore cutting-edge methodologies for ensuring the safety, functionality, and sustainability of innovative materials.

This immersive, hands-on training is co-organised by 15 leading EU-funded projects and provides a unique opportunity to bridge the gap between theory and real-world applications. Participants will engage with a variety of state-of-the-art topics , equipping them with the skills needed to drive responsible innovation.

📌 COST Session & Scholarships

A dedicated two-day COST session will be held on 10 and 11 July during the school. EuMINe will support up to 8 participants with scholarships covering travel reimbursement (according to COST rules) and a daily allowance for the 2 days.

🎯 Scholarships selection

Scholarships will be awarded based on several criteria, including affiliation with an Inclusiveness Target Country (ITC), gender, age, and short motivation statement explaining the applicant’s interest in the school and its relevance to their research or studies.

📚 Topics

  • Setting the scene: SSbD policy context in the EU

  • Environmental, health and safety assessment (Steps 1-3 of EC-SSbD framework), including:

    • Intrinsic hazard properties

    • New Approach Methodologies

    • Relevance of in vivo studies (invertebrate and vertebrate models)

  • Integrated Life Cycle Sustainability Assessment (ILCSA) (Steps 4-5 of the EC-JRC SSbD framework), including:

    • Environmental Life cycle assessment (LCA)

    • Social LCA

    • Lifecycle Costing

  • Integrating functionality considerations into SSbD workflows: the role of material characterization and the assessment of functional performance

  • Addressing the complexity of advanced materials and their interactions: Multiscale modelling and multidimensional analysis

  • Enhancing the uptake of SSbD by industry, especially SMEs: user-friendly decision support tools

📍 Venue

🌐 More Information

Full program and registration details available at:

👉 https://www.sunrise-horizon.eu/venice-training-school-2025

ML4MatSci: Hands-on Machine Learning for Research in Materials Sciences – 22-24 July 2025 (Aschaffenburg, Germany)

ML4MatSci School is designed to equip current and prospective PhD students with the essential knowledge and practical skills needed to apply machine learning techniques in the field of Materials Informatics. Through a combination of lectures, hands-on sessions, and collaborative discussions, participants will gain a solid foundation for integrating data-driven approaches into their research.

🎓 PhD School: Machine Learning in Materials Science

The PhD School equips participants 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, encouraging creativity, critical thinking, and innovation in applying data-driven approaches to materials science and related fields.

🔍 Key Scientific Focus Areas

  • Fundamentals of Machine Learning & Artificial Intelligence
    Core concepts, workflows, and practical considerations
  • Image Processing for Materials Characterization
    From segmentation to feature extraction in microscopy and beyond
  • Large Language Models (LLMs) & Their Emerging Applications
    Using LLMs for scientific text mining, synthesis, and discovery
  • Datasets, Data Quality & Evaluation Metrics
    How to prepare, validate, and measure the impact of your data
  • Bayesian Optimization & Active Learning
    Smart experimentation and efficient exploration of design spaces
  • Advanced Topics in AI-Driven Materials Science
    Including:
    • Generative models (e.g., for molecule or structure generation)
    • Explainable AI (XAI)
    • Multi-modal learning
    • AI for materials discovery pipelines

📝 Registration & Abstract Submission

Application

🗓️ Extended Deadline: 11 May 2025 26 May 2025
👉 Apply here

Recommended Prerequisites

To ensure participants can fully benefit from the school, we recommend the following:

  • A basic understanding of programming languages, preferably Python or a similar language.
  • Enrollment in, or preparation for, a PhD program in physics, solid-state chemistry, materials science, computer science, or a related field.

Financial Support

The EuMINe COST Action is pleased to offer reimbursement for up to 25 participants, covering travel expenses and daily allowances. Participants will be selected based on:

  • Interest in the school by submitting 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)

📅 Important Dates

  • Application Deadline: 11 May 2025 26 May 2025
  • Notification of Acceptance: 16 May 2025 28 May 2025

🎤 Lecturers

  • Jacob Goldberger, Bar-Ilan University (Israel)
  • Keith Butler, University College London (UK)
  • Pascal Friederich, Karlsruhe Institute of Technology (Germany)
  • Milica Todorović, University of Turku (Finland)
  • Patrícia Ramos, Polytechnic of Porto, INESC TEC (Portugal)
  • Michael Moeckel, Technische Hochschule Aschaffenburg (Germany)
  • Amila Akagic, University of Sarajevo (Bosnia and Herzegovina)

📌 Preliminary Programme

🗓️ Day 1 – July 22, 2025 (Aschaffenburg)

08:00 – 09:00Registration
09:00 – 09:30Welcome & Programme Overview
09:30 – 10:30Introduction to Machine Learning
10:30 – 11:001st Hands-on Session
11:00 – 11:30Coffee Break
11:30 – 12:00Introduction to Deep Learning & Computer Vision
12:00 – 13:002nd Hands-on Session: Medical Imaging & Explainable AI
13:00 – 14:00Break
14:00 – 15:00 Industry Session
15:00 – 16:00 Introduction to Unsupervised ML
16:00 – 16:30 Use Case: Additive Manufacturing
16:30 – 17:00Coffee Break
17:00 – 18:00Time Series & Forecasting
18:00 – 19:003rd Hands-on Session
19:00 – 20:00Elevator Poster Pitches (5 min each)
20:00 – 20:45Poster Session I & Reception

🗓️ Day 2 – July 23, 2025 (Würzburg)

08:00 – 09:00 Departure for Würzburg by bus or train
09:00 – 10:00 Arrival & Welcome
10:00 – 11:00 Datasets & Metrics
11:00 – 11:30 Coffee Break
11:30 – 12:00 Bayesian Optimization & Active Learning
12:00 – 12:304th Hands-on Session: Bayesian Optimization
13:00 – 14:00Break
14:00 – 14:30 Research at Promotionszentrum
14:30 – 15:30 Elevator Poster Pitches (5 min p.p.)
15:30 – 16:30 Poster Session II
16:30 – 17:00 Departure for Residence
17:00 – 20:30 Tour of Würzburg Residence
21:00 Departure from Würzburg

🗓️ Day 3 – July 24, 2025

08:30 – 09:30 LLMs for Materials Science
09:30 – 10:00 5th Hands-on Session on LLMs
10:00 – 10:30 Coffee Break
10:30 – 11:30 Advanced Topics
11:30 – 12:00 6th Hands-on Session: Advanced Topics
12:00 Departure from Aschaffenburg

👥 Local Organizers and Management

  • Michael Moeckel, Technische Hochschule Aschaffenburg (Germany)
  • Amila Akagic, Faculty of Electrical Engineering, University of Sarajevo (Bosnia and Herzegovina)
  • Francesco Mercuri, National Research Council in Bologna (Italy)
  • Local host: NISYS PhD school Aschaffenburg-Coburg-Würzburg

✈️ Getting to Aschaffenburg

Directions to Campus
(Würzburger Straße 45, Aschaffenburg)

✈️ Nearest Airport:

The closest airport is Frankfurt am Main (FRA). From there, you can reach Aschaffenburg Central Station by:

  • ICE high-speed train (approx. 1 hour)

  • Local train (HLB) (approx. 1 hour 15 minutes)

🚆By Public Transport:

Arrive at Aschaffenburg Central Station. From there, you have two easy options to reach the campus:

  • Take the regional train (direction: Miltenberg) and get off at Aschaffenburg Hochschule station.

  • Alternatively, take one of the following bus lines: 5, 15, 40, 41, 47, or 63. Get off at the “Hochschule” stop.

🚗By Car from Würzburg:

  • Take the A3 and exit at Aschaffenburg Ost
  • Follow the B26 and turn left onto Stengerstraße, continuing along the Südring
  • After about 2 km, take the exit for Würzburger Straße and turn left
  • Campus access: via Flachstraße, then turn left into Bessenbacher Weg

🚗By Car from Frankfurt/M.:

  • Take the A3 and exit at Aschaffenburg Stockstadt
  • Follow the B8 towards Mainaschaff, then take the B26 exit towards Darmstadt/Stadtring
  • Turn onto Westring and continue to Adenauerbrücke/Westring
  • Stay on Südring and follow signs to Haibach/Zentrum/Gailbach or Hochschule
  • Turn right onto Würzburger Straße
  • Campus access: via Flachstraße, then left onto Bessenbacher Weg