Welcome to a new addition of the NAISS training newsletter. Registration for our two last training events is closing soon:
- The NAISS introduction training days are aimed at new users of our infrastructure and users who are already using our foundation but require more guidance regarding the foundations of using an HPC service. Please feel free to attend those sessions which are important to you and skip the others.
- The course AI and HPC is aimed at users familiar with HPC, requiring an introduction to Deep Learning and how to run AI workloads on an HPC system.
If you want to speak to us in person, the next zoom-in is scheduled for the 11th of June.
We also invite you to training events provided by the Mimer AI Factory and by ENCCS.
If you have ideas, questions, requests or any other input, please get in touch, preferably using the NAISS support form in SUPR. We love to hear from you.
Overview
NAISS training
- Online training events for new users: NAISS Introduction training days, 1 - 3 June 2026
- Online/on-site course: AI and HPC, 3 - 5 June 2026, Stockholm and via zoom
Online interactive support and discussion forum
- NAISS Zoom-in - a virtual open-house, 11th June 2026 from 14:00 until 15:00
Mimer AI Factory events
- Webinar: Advanced image analysis and AI/ML for medical imaging: Methods for CT-based Large-Scale Body Composition Analysis, 27 May 2026
- Webinar: From Lab Data to AI-Ready Insights: An Introduction to NOMAD for Materials Science Researchers, 3 June 2026
- Online workshop: Introduction to MLOps, 8, 9, 11 June 2026
- Webinar: Trustworthy AI in practice, 16 June 2026
ENCCS events
- Workshop: Julia for High Performance Data Analysis, 26-29 May
NAISS training
Online training events for new users: NAISS Introduction training days, 1 - 3 June 2026
The NAISS introduction training days offers seven modules distributed over 3 days. Each module describes a particular aspect of the NAISS systems. You are welcome to choose and pick the modules that best address your existing knowledge, your interest and your requirements. For each module we provide a separate description, which should allow you to make an informed choice on the modules you wish to attend.
The course modules are particularly aimed at new users of the infrastructure. They are also suitable for experienced users, wishing to deepen their understanding of the workings of the systems.
The training week offers the following modules:
- Linux Command Line 101
- Connecting and File transfer
- Selecting software modules
- Running jobs on clusters
- Linux Command Line 202
Participants can attend as many of the modules as they wish.
For more information and access to registration visit the event page: NAISS Introduction training days (NAISS)
Online/on-site course: AI and HPC, 3 - 5 June 2026, Stockholm and via zoom
The term AI is nowadays often used interchangeably with Deep Neural Networks, a technology which is currently changing society as well as science and technology. There is a strong connection between AI and High Performance Computing (HPC) in that AI workloads often need to be, or are run on, HPC systems. Such workloads also turn out to be a particularly challenging application of HPC.
This hybrid (on location/online) course is at the beginners/intermediate level and is mainly intended for students familiar with HPC and in need of an introduction to Deep Learning and how to run AI workloads on HPC clusters. Some of the basic theory and models in deep learning will be covered as well as the techniques involved when running such models. The course includes practical exercises to deepen the understanding of the lectures. At the end of the course participants should be familiar with some of the concepts in deep learning, be able to run simple AI workloads and run them in parallel on an HPC system. The teaching language will be English.
For more information and access to registration visit the AI and HPC event page (NAISS).
Online interactive support and discussion forum
NAISS Zoom-in - a virtual open-house, 11th June from 14:00 until 15:00
You are invited to a virtual meeting room. Inside the meeting room we like to discuss services offered by NAISS and how they can be used for your computational needs, help you process your data and visualise your results. Participants are highly encouraged to pose their own questions.
We also expect to have experts available from C3SE, HPC2N, LUNARC and Berzeliusto discuss the University operated HPC services at Chalmers, Umeå and Lund University.
The zoom-link will be shared closer to the event.
The following NAISS Zoom-in sessions are planned for September
Mimer AI factory events
Webinar: Advanced image analysis and AI/ML for medical imaging: Methods for CT-based Large-Scale Body Composition Analysis, 27 May 2026
This webinar will present Artificial Intelligence for CT medical imaging, focusing on automated methods for large-scale body composition analysis. The presentation will introduce deep learning techniques for image segmentation, image registration and deep regression methods of CT images, enabling detailed assessment of tissues such as muscle, adipose tissue, and organs. Participants will gain insights into how AI can be used to automatically analyze CT scans for body composition, enabling research in metabolic diseases and population studies, and explore challenges and future directions in applying AI to large-scale body composition analysis.
Time: 27 May 2026, 10:00–11:30 (CEST)
Register on the AI/ML for medical imaging event page (MIMER AI).
Webinar: From Lab Data to AI-Ready Insights: An Introduction to NOMAD for Materials Science Researchers, 3 June 2026
Research in materials science generates vast amounts of experimental and computational data, but much of it remains siloed, poorly documented, or difficult to reuse. This webinar introduces the NOMAD platform, a free, open-source research data management ecosystem developed by the FAIRmat consortium, designed specifically for the materials science community. NOMAD enables researchers and R&D teams to store, structure, share, and publish their data following the FAIR principles (Findable, Accessible, Interoperable, and Reusable), thus transforming raw outputs into structured, high-quality datasets ready for collaboration and machine
learning applications.
Time: 3 June 2026, 11:00–12:30 (CEST)
Register on the NOMAD introduction event page (MIMER AI)
Online workshop: Introduction to MLOps, 8, 9, 11 June 2026
MLOps (Machine Learning Operations) is the set of practices that combines machine learning, software engineering, and DevOps to reliably build, deploy, monitor, and maintain ML models in production. It focuses on automation, reproducibility, and governance across the entire ML lifecycle. Thus, MLOps moves beyond individual steps and algorithms to provide a solid structure for ML development. In this event, we will guide you through the whole MLOps journey, examine its individual steps and provide a holistic view of the entire pipeline. The event combines interactive lessons with a hands-on lab where the participants will apply ideas from the course in practice. The event is a 3-half-days course running 9:00-12:00 on each day.
Time: 8 June 2026, 9 June 2026, 11 June 2026: 09:00–12:00 (CEST)
Register on the MlOps introduction event page (MIME AI).
Webinar: Trustworthy AI in practice, 16 June 2026
The webinar will begin with a short introduction to the EU AI Act and the core principles of Trustworthy AI. The team will present the Mimer Trustworthy AI Self-Assessment Tool (the SATisfiability), developed to support organizations in navigating these requirements. The tool is based on the ALTAI questionnaire and the EU AI Act, with further
development guided by forthcoming CEN-CENELEC standards. It provides users with a clear overview of how trustworthy their AI system or concept is, while highlighting the key regulatory and ethical requirements they should prioritize. Using this tool gets the users closer to understand their own developments in relation to
trustworthiness as well as the EU AI Act.
Time: 16 June 2026, 11:00–12:30 (CEST)
Register on the trustworthy AI in practice event page (MIMER AI).
ENCCS events
Workshop: Julia for High Performance Data Analysis, 26-29 May
Abstract: Julia is a modern high-level programming language that is fast (on par with traditional HPC languages like Fortran and C) and relatively easy to write like Python or Matlab. It thus solves the two-language problem, i.e. when prototype code in a high-level language needs to be combined with or rewritten in a lower-level language to improve performance. Although Julia is a general-purpose language, many of its features are particularly useful for numerical scientific computation, and a wide range of both domain-specific and general libraries are available for statistics, machine learning, and numerical modeling.
Join us for Julia for High Performance Data Analysis, a hands-on workshop designed to equip you with practical skills for working with large datasets, optimizing code, and leveraging Julia’s rich ecosystem of libraries. You’ll explore real-world applications in data analysis, numerical computation, and machine learning, all while discovering how Julia can streamline your workflow and elevate your performance without sacrificing code readability.
Detailed information can be found on the Julia for HPC workshop page (ENCCS).
Time: May 26-29, 9:00-12:00 (CET), 2026.