Collections

Use collections to bring together multiple datasets and their associated files in an almost unlimited number of ways.

Strategies for training and knowledge exchange with a consulting perspective

This workshop introduces evidence-based approaches to teaching, training development, consulting, and mentoring in technical and scientific environments. Participants will explore how people learn, how to design engaging and inclusive training sessions, and how to assess and address training needs effectively. The course also covers practical aspects of consultancy, including communication, project management, prioritisation, and balancing consulting activities with other professional responsibilities.

3 0 28 0

System administration for HPC

This advanced course introduces the core concepts and daily tasks of system administration in high-performance computing (HPC) environments. The materials cover workload management with Slurm, user and software management, containerised applications, automated configuration, and system monitoring. Through practical examples and hands-on exercises, participants will explore the tools and workflows used to operate reliable, scalable, and efficient HPC clusters. The course is aimed at Linux users, technical staff, and aspiring system administrators who want to better understand and support modern research computing infrastructure.

6 0 31 0

Code & Collaborate: The FAIRytale of Software Development

This course introduces the foundations of collaborative and FAIR software development for research and data science projects. You will learn how to use version control, collaborate on shared code, and organise software projects in a reproducible and maintainable way. The materials also cover software testing, documentation, dependency management, and reproducible development environments through practical hands-on examples. The course is aimed at researchers and developers with basic programming experience who want to improve collaboration and adopt more professional software development practices.

6 0 32 0

Applied Machine Learning for Biological Data

This course introduces the application of machine learning methods to biological and genomic data using Python (Module 1 gives you an overview of the Python workflow you need to know). The materials cover core concepts such as data handling, classification, regression, clustering, and deep learning, combining theoretical foundations with hands-on coding exercises on real-world datasets. Participants will work with widely used tools including NumPy, Pandas, and PyTorch while exploring reproducible workflows and modern computational approaches such as containerisation and GPU-accelerated analysis. The course is aimed at researchers and data analysts who want to apply machine learning techniques to biological research questions and large-scale genomics data.

0 2 31 0

Awareness in Data Management and Analysis for Industry and Research

This workshop covers essential research data management skills. The first part introduces data management fundamentals, best practices, European data spaces, and Data Management Plan creation. The second part focuses on practical implementation: data organisation, FAIR principles, Electronic Lab Notebooks, and reproducible data analysis using tools like Git, Zenodo, and Conda. Interactive exercises throughout help participants apply concepts to real-world research scenarios.

2 0 78 0

A practical introduction to bioinformatics and RNA-seq using Galaxy

This course provides a comprehensive introduction to RNA-sequencing (RNA-seq) data analysis using the Galaxy platform. Galaxy offers an accessible, user-friendly, and FAIR environment that empowers researchers without programming experience to perform complex bioinformatics analyses. The course begins with an introduction to Galaxy, followed by tutorials on sequencing quality control and read mapping. Participants will then learn both the foundational and advanced steps of RNA-seq data analysis, including quantification and differential expression. The course concludes with an overview of relevant data types, databases, and resources to support further exploration and interpretation of RNA-seq results.

12 0 115 0

Modeling and simulation of fluid-structure interactions across scales

In today's world, the modeling and simulation of complex systems span a wide range of disciplines, from biology and chemistry to engineering and beyond. Understanding these systems requires a multiscale approach that integrates knowledge from various levels of organization, from molecular interactions to macroscopic behavior. This approach is crucial for tackling challenges in diverse fields such as bioliquids, energy storage devices, and helicopter dynamics. In the realm of bioliquids, such as biomolecules and cellular components, multiscale modeling plays a pivotal role in unraveling the complexities of biological processes. From protein folding to membrane dynamics, researchers employ techniques ranging from atomistic simulations to coarse-grained models to capture the intricate interplay of molecules within cellular environments. These models not only enhance our fundamental understanding of biological systems but also have practical applications in drug design and personalized medicine. Similarly, the design and optimization of batteries demand a multiscale perspective to address issues ranging from electrode materials to system-level performance. Atomistic simulations provide insights into the behavior of ions and electrons within electrode materials, guiding the development of novel chemistries with enhanced energy storage capabilities. Meanwhile, continuum models facilitate the prediction of battery performance under various operating conditions, aiding in the design of safer and more efficient energy storage devices. In the field of helicopter dynamics, multiscale modeling enables engineers to simulate the interaction between aerodynamics, structural mechanics, and control systems. By integrating these disparate disciplines, engineers can optimize helicopter design for improved performance, maneuverability, and safety. Despite significant advancements, multiscale modeling of complex systems still faces challenges. Bridging the gap between different scales, accurately representing system dynamics, and incorporating uncertainty remain areas of active research. Furthermore, the increasing complexity of modern systems demands innovative computational techniques and interdisciplinary collaboration. In conclusion, the state of the art in multiscale modeling and simulation of complex systems encompasses a diverse range of applications, from bioliquids and batteries to helicopters. By integrating knowledge across multiple scales, researchers strive to unravel the mysteries of nature, optimize technological innovations, and address pressing societal challenges.

16 0 124 0

PSI schools

Video recordings and educational materials from schools at the Paul Scherrer Institute (PSI), Switzerland.

0 1 128 0

PWTK-2024: An Online Tutorial

The aim of the online PWTK-2024 tutorial is to teach participants how to use the PWTK scripting environment to effectively automate their Quantum ESPRESSO calculations by employing built-in workflows or creating their own. The tutorial will cover topics ranging from basic to more advanced scripting.

The tutorial consists of one hands-on session per day. Participants will use their laptops/desktops and will be given access to an HPC supercomputer to learn how to use PWTK on HPC machines.

Participants should have at least a basic knowledge of how to use Quantum ESPRESSO. Interested participants lacking Quantum ESPRESSO know-how can attempt to follow the first part of the online QE-2021 school before the PWTK-2024 tutorial.

6 0 167 0

MaX school: Materials and molecular modelling with QUANTUM ESPRESSO

The course encompasses a comprehensive curriculum designed to cover the primary features of the QUANTUM ESPRESSO code. The emphasis is on practical skill development. The course strikes a balance between theory and application, offering a hands-on learning experience. It caters to a beginner to intermediate level, aiming to equip participants with the fundamental knowledge and skills necessary for the effective utilization of QUANTUM ESPRESSO in their research and academic pursuits.

4 0 172 0

ML4MS Machine Learning Modalities for Material Science

A rooted knowledge and understanding of the material and its properties stems from a holistic perspective. Indeed, when discussing the properties of a newly engineered material, it is common to present:
a text-based description of the sequence of actions through which such material was obtained, listing key variables as scalars.
a characterization of its structure by means of advanced microscopy (e.g., 2D images, 3D tomographies, 4D spatio-temporal analysis) and spectroscopy (e.g., adsorption spectra, NMR spectra), also with the aid of atomistic and electronic structure simulations.
a list of key performance indicators, in the form of scalar variables (e.g. the mechanical properties of an alloy or the Seebeck coefficient of a thermoelectric) or a time-series (e.g., activity of a catalyst over time, the capacity of a battery over time).
a mechanistic discussion of the relationships that link structure-to-property, often through quantities extracted from electronic structure and atomistic scale simulations.

0 5 191 0

Efficient materials modelling on HPC with QUANTUM ESPRESSO, SIESTA and Yambo

This workshop will gave a broad overview of important fundamental concepts for molecular and materials modelling on HPC, with a focus on three of the most modern codes for electronic structure calculations (QUANTUM ESPRESSO, Yambo and SIESTA).

5 0 177 0