Building and sustaining a Community of computational biologists at EMBL through Consulting, Training, and Infrastructure

This demo showcases how EMBL’s DaSIS team enhances interdisciplinary research through four pillars: expert consulting, tailored training, robust bioinformatics infrastructure, and vibrant community building. By connecting researchers with specialized support in data analysis, coding, and project management, DaSIS fosters seamless collaboration and innovation. Attendees will learn about scalable support models, the value of research support careers, and strategies to build lasting scientific networks—insights relevant beyond life sciences to the broader research community.

Collaboration is essential in computational biology, where interdisciplinary approaches drive innovation and address complex challenges. At the European Molecular Biology Laboratory (EMBL), the Data Science Internal Support (DaSIS) strengthens this collaboration through four key pillars: consulting, training, infrastructure, and community building.
Consulting is central to our work, providing expert guidance on challenges ranging from statistical analysis and mathematical modeling to coding and project management. By connecting researchers with domain-specific experts across EMBL, we help facilitate impactful, collaborative projects.
Training empowers researchers to thrive in a fast-evolving landscape. We offer hybrid workshops, self-paced resources, and focused sessions on topics like programming, visualization, and machine learning. Our approach balances accessibility with depth, helping scientists stay at the forefront of their fields.
Robust infrastructure supports our mission. We maintain tools such as coding platforms, version control systems, and cloud-based environments tailored to bioinformatics. Combined with collaborative and communication platforms, these ensure seamless research workflows.
Community unites these efforts. We foster engagement through meetups, clubs, and knowledge-sharing forums that encourage connection, collaboration, and lasting professional networks.
While our work is rooted in life sciences, the challenges and strategies are relevant across disciplines. We share our approach at the Open Science Fair to promote broader dialogue on effective research support and to learn from others. Crucially, we advocate for research support as a vital, rewarding career in academia. By highlighting this work, we hope to inspire conversations about career development, institutional priorities, and how to better recognize and integrate support roles into the scientific ecosystem.