EVENTS

Introduction to Python for Computational Science (Part 1)
The course has been designed for researchers to learn practical programming skills that are relevant for use of data processing, data science and computation in domain specific contexts. The module does not assume prior programming knowledge of participants. The module uses hands-on activities for all participants to exercise and experiment with the taught material. The course introduces skills that are advantageous for data handling - be it from experiment or simulation – and provides a basis for self learning or directed learning of more specialised topics at a later stage.

Part 2 of the course provides a deeper look into Python and introduces a wider range of libraries.

Anticipated topics:

• Introduction to Python
• Data types & structures
• Control flow
• Functions
• PEP8
• Name spaces
• File Input/Output
• Numpy
• matplotlib
• unit tests
• virtual environments
• Spyder
• IPython
• Jupyter

Register here for part 1 (deadline is Wednesday 4 February 2026)

Dirk Feuchter from the Karlsruhe Institute of Technology will join us at the HiRSE Seminar Series to talk about “Before Distributing Research Software - Impulses from an RSE&TTO-Perspective”

Abstract: Before distributing research software, several considerations arise from both Research Software Engineering (RSE) and Technology Transfer Office (TTO) perspective. This talk addresses scenarios where RSEs approach the TTO to exploit and license RSE’s software to industry partners, spin-offs, or to explore via open-source business models. Let us outline the minimum requirements for a license-compliant software distribution and discuss whether RSEs can proactively collaborate on these preparations. Drawing on a common contribution to deRSE25, initial lessons learned will be shared, including essential information for source code files and tools such as Reuse and Fossology that might support for compliance. Finally, we highlight how to deal with emerging regulations like the Cyber Resilience Act or the new Product Liability Directive. The seminar is intended to encourage discussion on integrating compliance tools into development workflows to enhance sustainability and value of our research software developments.

Institutions

• Helmholtz Platform for Research Software Engineering - Preparatory Study

Building on Part 1, this course covers additional aspects:

1. advanced Python
2. additional libraries such as scipy, pandas, and sympy
3. research software engineering and testing, and
4. selected numerical methods and application examples with focus on natural science and engineering problems.

Aspects (1) to (3) are covered in the beginning of the course. Part (4) is delivered at the end of the week, and can be omitted if not relevant to the participant.

Anticipated topics:

• higher order functions
• programming paradigms
• scipy, pandas, sympy
• research software engineering practices, in particular testing
• Python package installation
• interpolation, root finding, curve fitting
• optimisation, computing derivatives
• integration of functions and ordinary differential equations

Register here for part 2 (deadline is Wednesday 18 February 2026)

We are calling in all AI enthusiasts in Hamburg. Let's talk and exchange thoughts and ideas!

Meet other AI and tech enthusiasts at our well-established AI Meetup, bringing together the Hamburg AI scene for more than three years. Join us for the AI Mix & Mingle at Sofabar, where you can chat casually, exchange ideas, or discuss your AI projects. There are no presentations—the focus is on networking and open conversation.

While your registration is not mandatory, it is appreciated. You would make our reporting easier if you sign up on Eventbrite. But feel free to drop by spontaneously, too, to connect with us and others, build networks, and dive into interesting conversations about AI and beyond!

We are lookimg forward to seeing you there!
For any questions, comments, or feedback, please email us at: cm@aric-hamburg.de
More information on our website: [https://aric-hamburg.de/veranstaltungen/ai-mix-mingle

Institutions

• Artificial Intelligence Center Hamburg (ARIC) e.V.

Cyber-physical systems are required to adapt to changing demands, often experience architectural changes over their lifetime, and generate a heterogeneous set of data. All of this leads to significant demands on monitoring and control software. This conference focuses on aspects of machine learning and related domains, such as predictive maintenance, self-optimization, fault diagnosis, re-planning, and reconfiguration. To build intelligent cyber-physical systems close cooperation between AI-research and industrial engineering is necessary. To facilitate such an exchange is the goal of this conference.

Register here: Registration

The 9th Machine Learning for Cyber Physical Systems (ML4CPS) conference offers researchers and users from various fields an exchange platform. The conference will take place March 2026, 19th till 20th at the Fraunhofer Forum in Berlin. Hosts are Fraunhofer IOSB, Helmut Schmidt University, Hamburg University of Technology, and the Chair of Production Engineering of E-Mobility Components (PEM) of RWTH Aachen.

In this year’s edition of the conference we also encourage submission of contributions from industry detailing scientific problems they encounter. To contribute, an extended abstract of a maximum of one page is required and must be submitted through the conference portal.

Institutions

• Fraunhofer IOSB
• Helmut-Schmidt-Universität Hamburg
• RWTH Aachen
• Hamburg University of Technology (TUHH)

We are calling in all AI enthusiasts in Hamburg. Let's talk and exchange thoughts and ideas!

Meet other AI and tech enthusiasts at our well-established AI Meetup, bringing together the Hamburg AI scene for more than three years. Join us for the AI Mix & Mingle at Sofabar, where you can chat casually, exchange ideas, or discuss your AI projects. There are no presentations—the focus is on networking and open conversation.

While your registration is not mandatory, it is appreciated. You would make our reporting easier if you sign up on Eventbrite. But feel free to drop by spontaneously, too, to connect with us and others, build networks, and dive into interesting conversations about AI and beyond!

We are lookimg forward to seeing you there!
For any questions, comments, or feedback, please email us at: cm@aric-hamburg.de
More information on our website: [https://aric-hamburg.de/veranstaltungen/ai-mix-mingle

Institutions

• Artificial Intelligence Center Hamburg (ARIC) e.V.

Are you passionate about exploring the intersection of digital technologies and the humanities? Join our PhD course ‘An Introduction to Digital Humanities and to the digital treatment of language data’ designed specifically for PhD students interested in applying digital methods to their humanities language data, and to thereby be able to answer new kinds of research questions on large amounts of such data. In this course, we will equip you with a basic understanding of various methods, standards, and tools essential for conducting digital humanities research on language data.

Our focus of the course will be on the digital processing of text and speech, exemplified among others through the extensive digital corpora available through The Department of Nordic Studies and Linguistics. You will have hands-on experience with the corpus tool Korp, enabling you to unlock valuable insights hidden within vast amounts of textual data. Additionally, we will look into natural language processing techniques, providing you with a practical introduction to zero-shot & few-shot prompting of large language models, and machine learning with Python. Finally, you will be introduced to modern prompting and RAG (Retrieval Augmented Generation) techniques for having large language models (LLMs) assist in annotating and analysing your material. You will get the opportunity to work with these tools also on your own data.

As part of the course, you will also be introduced to CLARIN, a digital platform renowned for its research infrastructure in linguistic data. Moreover, we recognize the importance of text standards and FAIR (Findable, Accessible, Interoperable, and Reusable) data in today's scholarly landscape. The course will introduce you to these concepts, equipping you with the knowledge to ensure your research adheres to the standards of data integrity and accessibility.

Max. numbers of participants: 25 Participants must submit 1/2 page abstract about their project and the digital language data which they apply. Please submit the abstract by email to phd@hrsc.ku.dk no later than 2 March 2026.

Please register via the link in the box no later than 9 February 2026. For more information about the PhD course, please contact the PhD Administration (phd@hrsc.ku.dk).

Institutions

• PhD School at the Faculty of Humanities at University of Copenhagen

The International Conference on Computational Science is an annual conference that brings together researchers and scientists from mathematics and computer science as basic computing disciplines, as well as from other various application areas, who are pioneering computational methods in sciences such as physics, chemistry, life sciences, and engineering, as well as in arts and humanitarian fields, to discuss problems and solutions in the area, identify new issues, and shape future directions for research.

ICCS 2026 in Hamburg, Germany will be the twenty-sixth edition in this series of highly successful conferences.

The conference theme for this year is “At the Forefront of Science through Computation and Data”.

This conference will be a unique event focusing on recent developments in: scalable scientific algorithms; advanced software tools; computational grids; advanced numerical methods; and novel application areas. These innovative novel models, algorithms and tools drive new science through efficient application in areas such as physical systems, computational and systems biology, environmental systems, finance, and others.

The Hamburg Network for Artificial Intelligence and Law (NAIL) will host a conference on “AI, Finance & Law: Innovation, Integrity, and the Future of Markets” on 2–3 July 2026 in Hamburg, Germany, and invites paper submissions.

This in-person conference will seek to explore a broad range of regulatory issues in relation to, inter alia, the following aspects:

• How should financial markets law respond to the adoption of AI systems by financial institutions and intermediaries? What are the economic effects of AI-driven financial markets, and are there risks to market integrity, efficiency, and to market stability?
• What governance mechanisms ensure accountability, transparency, and auditability of AI in financial services? How can market supervisors and investors effectively monitor the integrity of new AI-driven market players?
• How does the EU AI Act interact with existing and upcoming financial regulatory frameworks? How does the AI Act and associated rules apply to financial-markets use-cases such as algorithmic trading, risk models, and credit scoring?
• How can regulators balance innovation, competition, and financial stability in regulating AI? What forms of legal experimentation (sandboxing, testbeds, proportionality tools) support safe AI adoption and ensure innovation? 
• What are cross-border challenges with regulating AI across the EU and globally? What can the EU learn from global regulatory models such as the US, UK, Singapore, China, and international standard setters?
• Twin Transformation: How can advances in AI be balanced with sustainable development and green finance?

The conference organizers invite papers from scholars, policymakers, and practitioners on each of these topics, and on any other topic of relevance to the conference theme. In particular, the organisers encourage the submission of papers that examine these topics from an interdisciplinary, international and/or comparative perspective.

Institutions

• Network for Artificial Intelligence and Law (NAIL)

This Dagstuhl Seminar seeks to ignite a focused dialogue on the strategic positioning and practical implementation of digital transformation in scientific research. Central to our discussion will be the role of Digital Centers or Hubs as flagship components of modern research infrastructure and the significance of Research Software Engineering (RSE) and Research Data Management (RDM) as essential enablers of their success.

The seminar's guiding question is: How can digital transformation be effectively embedded in the research landscape? Should it be steered centrally via comprehensive digital centers or emerge through decentralized, institution-driven initiatives? We will explore the strengths, limitations, and potential synergies of both models, with the goal of deriving actionable insights for sustainable digital infrastructure strategies.

Another focus is on the tension between disciplinary specificity and transdisciplinarity: Should digital competence centers closely align with specific research domains, or should they work across disciplines to foster collaboration and shared innovation? Understanding this balance is crucial for building effective, scalable digital ecosystems across institutions and research communities.

For more information please read here

Institutions

• Indiana University - Bloomington, US
• Universität Kiel, DE
• Universität Innsbruck, AT
• HCDS, Universität Hamburg, DE