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Tag: machine learning

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

📍 Cluj-Napoca, Romania
📅 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.


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

🔍 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

💻 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!

📝 Application Details

🗓️ Extended Deadline: 31 May 2026 10 June 2026
👉 Apply now

💶 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

📅 Important Dates

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

📌 Programme

The complete programme will be available soon.

📍 Practical Information

Venue

Regele Ferdinand Conference Hall, USAMV
Calea Mănăștur 11
400394 Cluj-Napoca, Romania

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

📍 Sarajevo, Bosnia and Herzegovina
📅 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.

🔍 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

👥 Target Audience

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

📚 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

🔬 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

🧪 Teaching Format

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

  • 📚 Lectures – Advanced AI topics delivered by leading experts
  • 💻 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

👩‍🏫 Lecturers

  • Jacob Goldberger – Bar-Ilan University (Israel)
  • Keith Butler – University College London (UK)
  • Salim Belouettar – Luxembourg Institute of Science and Technology (Luxembourg)
  • Patrícia 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)

📌 Programme

🗓️ 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 Akagić Lecture
10:00 – 11:00 1st Hands-on Session — Hands-on
11:00 – 11:30 Coffee Break — 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 — Hands-on
13:30 – 15:00 Lunch — Break
15:00 – 15:30 Artificial Intelligence and HPC: Current Research Landscape and Opportunities Dr. Lemana Spahić 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 — Hands-on
17:30 – 18:00 Coffee Break — 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 — Reception

🗓️ 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 — Hands-on
11:00 – 11:30 Coffee Break — Break
11:30 – 12:30 Property-Guided Generative Models for Molecular Materials Discovery Patricia Ramos Lecture
12:30 – 13:30 5th Hands-on Session — Hands-on
13:30 – 15:00 Lunch — 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

🗓️ Day 3 – Friday, June 12, 2026

Venue: Faculty of Mechanical Engineering, Room “Svedski 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 — Hands-on
11:00 – 11:30 Coffee Break — 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 — Hands-on
13:30 – 15:00 Lunch — 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 — Hands-on
17:00 Closing and departure from Sarajevo Organizers Closing

📝 Application Details

🗓️ Deadline: 10 April 2026
👉 Apply now

📄 Required Documents

Applicants must submit:

  • Short CV (1 page)
  • Motivation letter (½ page)
  • Poster title and abstract (¼ page)
  • Travel cost estimate (in Eur)
  • Statement on participation without EU funding

💶 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)

📅 Important Dates

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

🧑‍💼 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)

📍 Practical Information

Location: Sarajevo, Bosnia and Herzegovina

Venue

Faculty of Electrical Engineering
University of Sarajevo
Kampus Univerziteta
71000 Sarajevo

📧 Contact:
Amila Akagic — 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 from September 24 to 26, 2025. The event is co-organized by the “European Materials Informatics Network” and the “Data-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.

📝 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

👉 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

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/]
Speaker: Andreas Tsoumanis

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, Andreas Tsoumanis

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 – 11:45
Hands-on Session on Isalos Analytics Platform – Part II
Speakers: Dimitra Danai Varsou, Dimitrios Mintis, Andreas Tsoumanis

11:45 – 12:00
Coffee Break

12:00 – 12:30
Monte Carlo methods: Macroscopic material properties from chemical constitution
Speaker: Prof. George Boulougouris

12:30 – 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
Innovative Materials Modeling: Correlative Microstructure Prediction and Ab-initio Chemical Accuracy
Speakers: Theodoros Tsatsoulis, C.A. 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)
  • Dr. Andreas Tsoumanis (NovaMechanics Ltd, Cyprus)
  • Mrs. Maria Modestou (NTUA, Greece)
  • Mr. Savvas Orfanidis (NTUA, Greece)
  • Prof. George Boulougouris (DUTH, Greece)

🏨 Venue & Accommodation

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

📋 Committees

Organizers:

  • Dr. Antreas Afantitis (NovaMechanics Ltd, Cyprus)
  • Dr. Panagiotis Kolokathis (NovaMechanics MIKE, Greece)
  • Dr. Francesco Mercuri (CNR, Italy)
  • Dr. Andrea Lorenzoni (CNR, Italy)

Selection Committee:

  • Dr. Antreas Afantitis (NovaMechanics Ltd, Cyprus)
  • Dr. Konstantinos Papavasileiou (NovaMechanics MIKE, Greece)
  • Dr. Panagiotis Kolokathis (NovaMechanics MIKE, Greece)

Local Organization & Management:

  • Dr. Antreas Afantitis (NovaMechanics Ltd, Cyprus)
  • Dr. Panagiotis Kolokathis (NovaMechanics MIKE, Greece)

✉️ Contact

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

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 – Registration
09:00 – Welcome & Program Overview
09:30 – Introduction to Machine Learning I (Michael Moeckel, Patricia Ramos)
10:30 – 1st Hands-on Session
11:00 – Coffee Break
11:30 – Introduction to Deep Learning and Computer Vision with Applications in Medical Imaging and Explainable AI (Amila Akagić)
12:00 2nd Hands-on Session: Medical Imaging & Explainable AI
13:00 Break
14:00 Industry Session (Jorrit Voigt)
15:00 – Introduction to Machine Learning II (Michael Moeckel)
16:00 – Use Case: Additive Manufacturing
16:30 – Coffee Break
17:00 – Generative Modelling for Property Driven Molecular and Material Discovery (Patricia Ramos)
18:00 – 3rd Hands-on Session
19:00 – Elevator Poster Pitches
20:00 – Poster Session I & Reception

🗓️ Day 2 – July 23, 2025 (Würzburg)

07:45 – Departure from Aschaffenburg to Wuerzburg by bus
09:00 – Arrival & Welcome
10:00 – Uncertainty Calibration (Jacob Goldberger)
11:00 – Coffee Break
11:30 – Bayesian Optimization & Active Learning for Autonomous Decision Making in Materials Optimization (Pascal Friedrich)
12:00 – 4th Hands-on Session: Bayesian Optimization
13:00 – Break
14:00 – On Multilingual Foundation Models (Goran Glavaš)
14:30 – Elevator Poster Pitches
15:30 – Poster Session II
16:30 – Departure and short walk to Wuerzburg residence
17:00 – Guided excursion at the residence: ML4Materials in artwork conservation and reconstruction
18:00 – Free time for socializing, sightseeing and dinner in Wuerzburg
21:00 Departure from Wuerzburg to Aschaffenburg by bus

🗓️ Day 3 – July 24, 2025

08:30 – LLMs for Materials Science (Keith Butler)
09:30 – 5th Hands-on Session on LLMs
10:00 – Coffee Break
10:30 – Advanced Topics (Milica Todorović)
11:30 – 6th Hands-on Session: Advanced Topics
12:00 Closing and 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