Graduate School of health and Medical Sciences

Login for PhD students at UCPH Login for others

HPC Launch
Provider: Faculty of Health and Medical Sciences

Activity no.: 3948-26-00-00	There are 25 available seats
	Enrollment deadline: 23/04/2026

Date and time	21.05.2026, at: 08:45 - 22.05.2026, at: 16:30
Regular seats	25
Course fee	2,880.00 kr.
Lecturers	Anders Krogh
ECTS credits	1.50

Contact person	HeaDS Administration E-mail address: heads-admin@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration SUND E-mail address: phdkursus@sund.ku.dk

Enrolment guidelines This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee. Learning objectives By the end of the course, participants will be able to: Understand HPC systems • Explain the purpose, structure, and key components of HPC platforms. • Identify suitable HPC resources and storage for different projects. Set up computing environment essentials • Use terminal commands, SSH, terminal multiplexers (e.g., tmux), and IDEs (like Visual Studio Code) effectively. • Track changes using version control with Git for collaboration (e.g., GitHub). • Manage software and data analyses via best practices (e.g., conda) • Execute computations by submitting and managing jobs with scheduler systems (e.g., SLURM). Manage computational projects with a research data management (RDM) focus • Plan for compute and storage resource needs for a project’s lifetime. • Plan and structure projects with organized files and templates (e.g., Cookiecutter). • Document projects by following metadata standards for reproducibility and reuse (e.g., ontologies). • Manage storage, archive projects and optimize HPC storage use. Content The goal of HPC-Launch is to equip researchers with the skills to start or reconfigure biological/health data projects using modern computing and research data management practices. The course consists of two integrated modules: • High-Performance Computing (HPC): Develop a practical understanding of HPC platforms, covering system structure, job scheduling, and tools for efficient interaction (e.g., SSH, tmux, IDEs). The module bridges technical gaps for beginner to intermediate users and introduces computing resources available to Danish researchers. • Research Data Management (RDM): Highlight the importance of good RDM practices and provide hands-on strategies for structuring projects, documenting data and metadata, applying version control, and archiving results for collaboration and reuse. Participants will gain: • Confidence in navigating HPC systems and running analyses efficiently • Tools and practices for managing files, projects, and data reproducibly • Experience applying concepts through exercises on the UCloud HPC platform (SDU) using bash and relevant IDEs In summary, HPC-Launch focuses on the efficient use of HPC resources for complex health data science projects, while also providing an overview of best practices in research data management. The course combines theory, case discussions, and hands-on exercises to strengthen participants’ ability to design efficient projects, conduct large-scale analyses, and ensure the long-term usability and reproducibility of data and results. HPC-Launch is the first course of a series we are developing to elevate practical technical skills in health data science, and is the intended prerequisite for HPC-Pipes (focused on environment management and bioinformatics pipeline languages). Participants Seats: 25 Target trainee Researchers and students who mainly rely on their own laptops for analysis, have little experience with HPC, or feel unsure about working directly on servers, but have large datasets / sensitive data / resource-intensive tools to handle in their research. They seek a more professional and reproducible environment for their analyses but may lack confidence or familiarity with command-line workflows and remote computing systems. Requirements The workshop is for PhD students and researchers at SUND who seek to acquire skills in effectively managing data and computing projects. The course is targeted to students performing data analysis on biological data or within the field of data science. Prior computational experience is required – we expect you to be comfortable independently programming in RStudio or Jupyter Lab before you sign up for the course. Basic knowledge of bash is also highly recommended for the demo session. Laptops will be required for all hands-on exercises. If you cannot easily install software on your laptop or lack administrative rights, please let the course organizers know when you sign up. Relevance to graduate programs The course is relevant to PhD students from the following graduate programs at the Graduate School of Health and Medical Sciences, UCPH: Biostatistics and Bioinformatics Basic Metabolic Research All graduate programmes Language English Form Lectures with active discussion sessions, interactive demos using the UCloud platform, and group work and exercises navigating UCloud and practicing with tools for RDM-compliant project set-up. Course director Anders Krogh, Professor, Head of Center for Health Data Science, Head of Health Data Science Sandbox Center for Health Data Science, anders.krogh@sund.ku.dk Teachers The workshop is provided by project members of the Health Data Science Sandbox, a national training and research infrastructure project. The Sandbox team is building training resources and guides for learning bioinformatics, predictive modeling in precision medicine, high performance computing and data carpentry. These resources are accessible to all Danish university employees (PhD students and up) via academic supercomputing infrastructure. Jennifer Bartell PhD, Senior consultant and Sandbox project manager Center for Health Data Science, KU bartell@sund.ku.dk Alba Refoyo Martinez PhD, Data Scientist, Sandbox Team Center for Health Data Science, KU alba.martinez@sund.ku.dk Dates 21-22 May 2026 Course location Faculty Club 16.6.16 Faculty of Health and Medical Sciences, Panum, Blegdamsvej 3B, 2200 København. Registration Please register by 23 April 2026 Expected frequency This course will likely be repeated in Spring 2027. Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrollment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

Click the search button to search Courses.

See which courses you can attend and when

Jan	Feb	Mar	Apr
May	Jun	Jul	Aug
Sep	Oct	Nov	Dec