SciLifeLab Training Hub: Roadmap and Work Programme release

The Roadmap highlights the Training Hub’s commitment to advancing scientific knowledge and skills through a multidisciplinary approach. It emphasizes the importance of fostering collaboration among researchers, educators, healthcare, and industry professionals to drive innovation and address critical challenges in life sciences and related fields. In addition, the Training Hub has the ambition, through various capacity-building initiatives, to meet the increasing challenges to develop and make the Infrastructures in SciLifeLab sustainable.

The four strategic objectives outlined in the Roadmap are initiatives focusing on the following:

  • Strategic Objective 1 focuses on establishing a cohesive Training Platform infrastructure by seamlessly integrating technical services and resources. This objective aims to create an interconnected system of Training Platform services, forming an openly available infrastructure that benefits both the SciLifeLab ecosystem and external life science communities. The ultimate goal is to position SciLifeLab as a Research Infrastructure, a recognized training provider for life sciences, supporting technological advancements and data-driven research.
  • Building knowledge and skills across the SciLifeLab ecosystem is the focus of Strategic Objective 2. The Training Hub aims to curate openly available and FAIR (Findable, Accessible, Interoperable, and Reusable) training collections, catering to the needs of the internal SciLifeLab ecosystem and extending its reach to external stakeholders, including universities, research institutions, healthcare and industry as well as international organizations. By fostering collaboration and knowledge dissemination, SciLifeLab aims to enhance lifelong learning opportunities for the life science community.
  • Strategic Objective 3 emphasizes the importance of quality and assurance in promoting standards and best practices for Open Science, Open Education, and FAIR principles. The Training Hub recognizes its role in driving the adoption of these standards across the SciLifeLab ecosystem and aims to actively participate in ongoing initiatives, working groups, and focus groups at both European and Swedish levels leveraging the outputs from this work back to the Swedish life science research community. By implementing and adapting these standards, the Training Hub seeks to support trainers and learners, ensuring a robust and transparent learning environment.
  • The establishment of a sustainable organization dedicated to training is at the core of Strategic Objective 4. This objective encompasses the Training Hub’s internal structure and operations, as well as its collaboration with key stakeholders such as infrastructure platforms, SciLifeLab sites, Capabilities, and management. The Training Hub aims to foster a culture of peer-to-peer learning, promoting the delivery of high-quality training by the broader SciLifeLab ecosystem. By integrating standards, tools, and resources, the Training Hub strives to create a supportive and collaborative community.

Associate Professor Jessica Lindvall, Head of Training, expresses enthusiasm about the published Roadmap and Work Programme, stating, “We are excited to embark on this transformative journey and shape the future of scientific training and lifelong learning. Through our strategic initiatives, SciLifeLab aims to empower researchers and staff scientists with the skills, knowledge, and networks they need to address global challenges and make significant scientific advancements.”

The publication of the Roadmap and the accompanying 5 year Work Programme has garnered widespread interest and support from the SciLifeLab ecosystem and the scientific community as well as educational institutions. It sets the stage for a dynamic and collaborative decade ahead, driving the advancement of life sciences and fostering a culture of lifelong learning.

Please refer to the publications with the citations: 


Last updated: 2023-05-30

Content Responsible: victor kuismin(