Stockholm (Lidingö). On-site 19 March 2026. Online dates 16 Feb – 17 April

• Course information: https://scilifelab-training.github.io/open-science/2603/
• Course leader: Ineke Luijten, ineke.luijten@scilifelab.se, Stockholm University 
• Content highlights: Good research practice; Open Science implications for project planning and study design; Open Access publishing and sharing of research outputs; Researcher evaluation and incentives; Citizen science and public engagement.
• Teaching activities: Pre-course self-study assignments; one full day of in-person lectures with interactive elements (polls, group work, and discussions); post-course assignment.
• Date: on-site 19 March 2026. Online dates 16 Feb – 17 April.
• Venue: DDLS RS Annual Meeting (Skogshem & Wijk, Lidingö)

Stockholm (Albano). On-site 8-12 June 2026. Online dates 8/6-12/6

• Course information: https://stockholmuniversity.box.com/s/efs6jjjj2ctvxuu0f1lcntq41oi86lpl
• Course leader: Chun-Biu Li, cbli@math.su.se, Department of Mathematics, Stockholm University
• Content highlights: This course provides a comprehensive training on how to practically train and use DNNs properly for statistical modeling. To be self-contained, an overview of basic concepts of DNNs relevant to life science applications will be included in the course. Instead of mathematical technicalities, the course will focus on establishing intuitive but deep understanding of the training and validation processes of DNNs.
• Teaching activities: On-site and online lectures, group discussion and projects, presentations and social events
• Date: on-site 8-12 June 2026. Online dates TBD.
• Venue: Campus Albano, Stockholm University, Stockholm

Stockholm (SciLifeLab). On-site 19-23 October 2026. Online dates TBD.

• Course information: https://uppsala.instructure.com/courses/122228
• Course leader:  Elin Kronander, NBIS, Uppsala University
• Content highlights: FAIR policy and practice; Organize files, data, and projects; Public repositories for data and code; Version control system; Package managers; Workflows; Jupyter notebooks
• Teaching activities: pre-course assignments, one week on-site with lectures and exercises, post-course assignments
• Date: on-site 19-23 October 2026. Online dates TBD.
• Venue: SciLifeLab Stockholm/Solna

Stockholm. On-site 19 March 2026. Online dates 20 Feb to 10 April (preliminary).

• Course information: detailed course information TBD
• Course leader: Heidi Carmen Howard, Heidi.howard@scilifelab.se, Chalmers University of Technology, 
• Content highlights: This 1 credit course “AI, You and Society” is designed to introduce DDLS research school doctoral students to reflect on the “Ethical, Legal and Social Issues” (ELSI) relevant to AI, especially in their own research and education but also for AI products being used more generally in society.  The course covers tools used to address the ELSI and governance of AI, including reflective questions, principles, guidelines and laws. Students will be guided through different modes of learning, including interactive online and in-person lectures, preparatory readings, case studies, case presentations, and group discussions. Themes addressed will include: the use of AI decision-aids in health care and how this can impact the autonomy of users; the use of AI in research and publishing and potential de-skilling; as well as issues around transparency and AI literacy in society.
• Teaching activities: The course will include one full day (8 hour) in-person session, as well as 3 online 1-2 hour sessions. 
• Date: on-site 19 March 2026. Online dates 20 Feb to 10 April (preliminary).
• Venue: DDLS RS Annual Meeting (Skogshem & Wijk, Lidingö)

Uppsala (BMC). On-site 4-8 May 2026. Online dates TBD.

• Course information: https://uppsala.instructure.com/courses/122258
• Course leader: Olga Dethlefsen & Payam Emami, olga.dethlefsen@scilifelab.se, payam.emami@scilifelab.se, Department of Biochemistry and Biophysics (DBB), Stockholm University, National Bioinformatics Infrastructure Sweden (NBIS), SciLifeLab
• Content highlights: End-to-end ML framework; Data preprocessing and feature engineering; Unsupervised and supervised learning; Specialized modeling settings (mixed-effects, survival); Model evaluation and interpretation; Multi-omics integration; Life science applications
• Teaching activities: two preparatory online sessions, a one-week on-site course including lectures, hands-on exercises, and group work, and a concluding online session for follow-up and discussion.
• Date: on-site 4-8 May 2026. Online dates TBD.
• Venue: BMC, Uppsala

Linköping University, Campus Valla. On-site 14-18 September 2026. Online dates TBD (starts late August).

• Course information: https://www.ida.liu.se/~olesy12/tlcourse/ and here
• Course leader: Oleg Sysoev, oleg.sysoev@liu.se, Linköping University
• Content highlights: This course will cover the main frameworks of transfer learning and their applications in Data-Driven Life Science.
• Teaching activities: Lectures, Labs, Project work
• Date: on-site 14-18 September. Online dates TBD (starts late August).
• Venue: Campus Valla, Linköping University, Linköping

Stockholm, Campus Solna. On-site 23-27 November 2026. Online dates 16/11-20/11.

• Course information: View Course information
• Course leader: Carsten Daub, carsten.daub@ki.se, Karolinska Institutet 
• Content highlights: Learn about critical aspects of experiment design for your genomics projects 
• Teaching activities: analyze experiment designs, lectures on experiment design, make your own experiment design 
• Date: on-site 23-27 November 2026. Online dates 16-20 November.
• Venue for Week 2: Air/Fire, SciLifeLab, Campus Solna

• Course leader: Ineke Luijten, Stockholm University
• Content highlights: Good research practice; What is Open Science; Open Science implications for study design and planning, and for sharing and publishing of data and results; Citizen science
• Teaching activities: pre-course assignments, one day of lectures with interactive sessions, post-course assignments
• Date: March 2025, same date as the DDLS RS Annual Meeting
• Venue: Djurönäset (at DDLS RS Annual Meeting)

• Course leader: Chun-Biu Li, Stockholm University
• Content highlights: Machine learning; Network architectures; Training and evaluation; Troubleshooting; Life Science applications
• Teaching activities: pre-course assignments, one week on-site with lectures and exercises using your own data, post-course assignments
• Date: May-June 2025
• Venue: Stockholm University

• Course website: https://uppsala.instructure.com/courses/111591
• Course leader: Elin Kronander, NBIS, Uppsala University
• Content highlights: FAIR policy and practice; Organize files, data, and projects; Public repositories for data and code; Version control system; Package managers; Workflows; Jupyter notebooks
• Teaching activities: pre-course assignments, one week on-site with lectures and exercises, post-course assignments
• Date: September-October 2025
• Venue: SciLifeLab Stockholm/Solna