Aziz Mithani, Scientific Training Lead for the EMBL-EBI Training Team, explains more about the Computational Biology Training in Hematology (CBTH) programme: a collaboration between EMBL-EBI and the European Hematology Association (EHA).

As data science and AI become increasingly central to addressing complex research questions, the need for computational expertise in hematology is greater than ever. In response to this need, the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI) and the European Hematology Association (EHA) launched the Computational Biology Training in Hematology (CBTH) programme. This specialised training and mentorship initiative equips early-career hematology researchers with the essential data science skills they need to drive forward research and innovation in blood-related diseases.

How did the CBTH collaboration come about?

CBTH was born from a shared vision between EMBL-EBI and EHA to address a critical skills gap in the field. As high-throughput data and AI continue to revolutionise research, hematology increasingly relies on computational methods to process and interpret complex datasets.

EMBL-EBI and EHA joined forces to provide a structured programme that combines technical training with hands-on mentorship. Together, they aim to empower clinicians and researchers to apply computational biology methods to some of hematology’s most challenging questions.

Programme goals: training a new generation of computational haematologists

The CBTH programme consists of two multi-day workshops in a European city, with a follow-up session at the EHA Congress held between the two workshops.

Through CBTH, EMBL-EBI and EHA aim to:

• Drive progress in hematological research: By equipping participants with computational skills, CBTH encourages the use of data science to advance knowledge of hematological disorders and improve management strategies.

• Equip researchers with essential computational skills: The programme offers practical training in data analysis and machine learning, with a focus on real-world applications in hematology.

• Foster impactful mentorship: Mentorship is a key component, enabling participants to connect with leading faculty in hematology. Through regular guidance, scholars gain new skills and insights tailored to their research, supporting both their professional and personal growth.

CBTH’s emphasis on mentorship provides scholars with personalised guidance throughout the year, fostering relationships with experts who offer critical insights into the computational aspects of hematology. This guidance enables scholars to enhance both their technical skills and their understanding of the clinical applications of computational research. By accessing this valuable support network, CBTH scholars are better equipped to overcome computational challenges in their work.

Future opportunities and expanding the CBTH community

A list of past awardees can be accessed here. The 2025 cohort has been selected following the application process, which closed on 24th September. The applications for the 2026 cohort will open in April 2025. As CBTH continues to grow, EMBL-EBI and EHA are planning to bring together scholars and alumni from CBTH and other EHA mentorship programmes, providing researchers with more opportunities to gain computational expertise and connect with like-minded professionals.

This ongoing programming ensures that participants not only acquire new skills but also build lasting networks that support their careers in hematology.

Stay tuned to the EMBL-EBI and EHA websites for announcements on upcoming cycles, application deadlines, and eligibility requirements.

In summary, CBTH is an exciting and transformative programme, offering researchers countless opportunities for professional development, research advancement, and personal growth. If you’re a hematology researcher eager to harness the power of data science, the CBTH programme is an excellent step toward becoming a leader in this dynamic and data-driven field.