We are thrilled to announce the upcoming BioSB Summer School on Advanced Machine Learning and AI for Life Sciences. Set in the beautiful forests surrounding De Werelt in Lunteren, The Netherlands, the programme runs from Sunday August 23 (end of afternoon) – Thursday August 27 2026.
The application process has been closed on Thursday 28 May 2026. See below for more information on the original application procedure, timelines, and costs.
The detailed course program and materials can be found here.
Course description
The BioSB Summer School on Advanced Machine Learning and AI for Life Sciences is an intensive four-day programme (Monday–Thursday, single track) designed for researchers who are ready to go beyond the basics and engage with the cutting edge of AI and ML in the life sciences. Participants arrive on Sunday afternoon for a welcome dinner and to settle in before the programme begins on Monday morning.
The programme strikes a 50/50 balance between theory and hands-on practice, ensuring participants not only understand modern methods but can apply them. The computational and methodological depth is central; biology serves as the motivating context throughout.
Topics covered include:
- Explainable AI
- Generative models
- Scientific machine learning
- Multi-modal learning
- Foundation models
- Representation of biological entities for deep learning
Applications span a range of life-science domains, including molecular and structural biology, and single-cell biology.
The school aims to expose participants to the most recent advances in machine learning and AI for the life sciences, equipping them with both the conceptual understanding and practical skills to apply these methods in their own research.
Course credits
Following the summer school corresponds to 1.2 ECTS.
Organising committee
- Dr. Perry Moerland (Amsterdam UMC; course coordinator)
- Prof. dr. Aalt-Jan van Dijk (University of Amsterdam)
- Dr. Federica Eduati (Eindhoven University of Technology)
- Yiting Shen (Amsterdam UMC)
Teaching staff
The following expert lecturers contribute to the summer school.
- Dr. Stavros Makrodimitris (University of Amsterdam)
- Dr. Wilson dos Santos Silva (Utrecht University)
- Dr. Shauna O’Donovan (Eindhoven University of Technology)
- Prof. dr. Sanne Abeln (Utrecht University)
- Dr. Pavel Sinitcyn (Utrecht University)
Together with those (co-)developing and assisting with the hands-on sessions (selection).
- Dr. Amelia Villegas Morcillo (Leiden University Medical Center)
- Larissa de Ruijter (University of Amsterdam)
- Petrus Bult (Eindhoven University of Technology)
- Max de Rooij (Eindhoven University of Technology)
- Catherine Chia (Radboud University Medical Center & Erasmus Medical Center)
Course program
The day-by-day program consists of a mix of lectures and hands-on sessions. On Monday and Tuesday there will be a poster session where participants present their research projects and ideas of how ML/AI methods may benefit their research. Lectures and hands-on sessions provide a state-of-the-art perspective on recent applications of ML/AI in the life sciences.
The detailed course program can be found here.
Target audience
The summer school is aimed at PhD students, academic researchers and industry participants with an intermediate level knowledge of machine learning, practical experience with programming in Python, preferably some previous exposure to deep learning, and a solid background in linear algebra and statistics. To help participants prepare, background material on (deep) neural networks, CNNs, and related topics will be made available prior to the start of the school.
Learning objectives
- Establish a shared methodological baseline; understand how biological data shapes the choice of representations and model architectures.
- Interpret and critically evaluate model predictions using explainable AI techniques.
- Understand and apply state-of-the-art generative approaches across biological sequences, omics data, and structures.
- Apply scientific machine learning approaches that integrate domain knowledge with data-driven methods.
- Combine heterogeneous (biological) data modalities.
- Understand the architecture and scope of biological foundation models; apply, fine-tune and critically evaluate them for downstream biological tasks.
Application and selection process (closed on 28 May)
Due to high demand and limited capacity, we expect to receive significantly more applications than available spots. Therefore, a selection process will take place.
You can start the application process via this link (free of charge). Registration is open until Thursday 28 May 2026.
After submitting the registration form, you will receive a confirmation email containing a link to the technical skills self-assessment, which must also be completed as part of your application.
Candidates who have completed the entire procedure – the registration form and the self-assessment – will be notified on Friday 29 May 2026 whether they have been selected.
Selected candidates will receive payment instructions at that time. The participation fee is €620 (academic) or €930 (industry), both excluding 21% VAT. This includes accommodation (private room), meals, and social activities. Your place will only be confirmed once payment has been received by Thursday 11 June 2026.
Applications will be evaluated based on:
- Motivation: clear articulation of course benefits and career impact
- Research relevance: alignment between current/planned research and course content
- Technical skills background: programming skills and relevant machine learning experience
- Cohort diversity
Venue
The summer school will be held at De Werelt, a conference and residential centre nestled in the forests on the edge of the Veluwe, near Lunteren, The Netherlands. De Werelt offers a peaceful and inspiring setting, well-suited to an intensive learning programme.
Participants will be accommodated on-site in private rooms. All meals and social activities during the school are included in the participation fee, creating an immersive environment that encourages interaction and collaboration among participants and lecturers throughout the week.
Getting there:
By public transport: Lunteren is served by the Valleilijn, a regional train operated by Connexxion. You can reach Lunteren by train from Amersfoort or Ede-Wageningen. If you are using an OV-chipkaart, note that you need to check out and check back in again at the Connexxion validator when transferring to this regional line. From Lunteren station, De Werelt is a 15–20 minute walk.
From Schiphol Airport, the journey to Lunteren takes approximately 1 hour and 40 minutes, travelling via Utrecht Centraal. From Amsterdam Centraal, the journey takes approximately 1 hour and 20 minutes. Being located at the center of the Netherlands, De Werelt is also well connected to other major Dutch cities.
By car: De Werelt is easily accessible via the A1, A12, and A30 motorways, and 400 free parking spaces are available on-site.
Additional information
For more information about the summer school, contact the organisation team via biosb-summerschool@googlegroups.com.
Funding
This summer school has been made possible thanks to support by the Dutch Research Council (NWO) via the TDCC-LSH Challenge project ‘Training the next generation of FAIR-aware and AI-savvy data scientists for the LSH domain‘.
