The identification of strategies by which to increase the representation of women and increase diversity in STEM fields (science, technology, engineering and mathematics), including medicine, has been a pressing matter for global agencies including the European Commission, UNESCO and numerous international scientific societies. In my role as UCL training lead for CompBioMed, a European Commission Horizon 2020-funded Centre of Excellence in Computational Biomedicine (compbiomed.eu), and as Head of Teaching for Molecular Biosciences at UCL from 2010 to 2019, I have integrated research and teaching to lead the development of high-performance computing (HPC)-based education targeting medical students and undergraduate students studying biosciences in a way that is explicitly integrated into the existing university curriculum as a credit-bearing module. One version of the credit-bearing module has been specifically designed for medical students in their pre-clinical years of study and one of the unique features of the course is the integration of clinical and computational aspects, with students obtaining and processing clinical samples and then interrogating the results computationally using code that was ported to HPC at CompBioMed's HPC Facility core partners (EPCC (UK), SURFsara (The Netherlands) and the Barcelona Supercomputing Centre (Spain)). Another version of the credit-bearing module has, over the course of this project, evolved into a replacement for the third year research project course for undergraduate biochemistry, biotechnology and molecular biology students, providing students with the opportunity to design and complete an entire specialist research project from the formulation of experimental hypotheses to the investigation of these hypotheses in a way that involves the integration of experimental and HPC-based computational methodologies. Since 2017–2018, these UCL modules have been successfully delivered to over 350 students—a cohort with a demographic of greater than 50% female. CompBioMed's experience with these two university modules has enabled us to distil our methodology into an educational template that can be delivered at other universities in Europe and worldwide. This educational approach to training enables new communities of practice to effectively engage with HPC and reveals a means by which to improve the underrepresentation of women in supercomputing.

确定提高妇女在 STEM 领域（科学、技术、工程和数学）（包括医学）中的代表性和多样性的战略，一直是包括欧洲委员会、联合国教科文组织和众多国际科学协会在内的全球机构的当务之急. 我在 CompBioMed 担任 UCL 培训负责人，这是一个由欧盟委员会 Horizo​​n 2020 资助的计算生物医学卓越中心 (compbiomed.eu)，并于 2010 年至 2019 年担任伦敦大学学院分子生物科学教学负责人，我整合了研究和教学以作为学分模块明确整合到现有大学课程中的方式，引领针对医学生和生物科学本科生的基于高性能计算 (HPC) 的教育的发展。一个版本的学分模块专为医学生的临床前学习而设计，该课程的独特之处之一是临床和计算方面的整合，学生获取和处理临床样本，然后使用在 CompBioMed 的 HPC 设施核心合作伙伴（EPCC（英国）、SURFsara（荷兰）和巴塞罗那超级计算中心（西班牙））移植到 HPC 的代码以计算方式询问结果。在这个项目的过程中，另一个版本的学分模块已经演变成替代本科生物化学、生物技术和分子生物学学生的第三年研究项目课程，为学生提供设计和完成整个专业研究项目的机会，从实验假设的制定到对这些假设的调查，涉及整合实验和基于 HPC 的计算方法。自 2017-2018 年以来，这些 UCL 模块已成功交付给 350 多名学生——这一群体的女性人口超过 50%。CompBioMed 在这两个大学模块方面的经验使我们能够将我们的方法提炼成一个教育模板，可以在欧洲和世界各地的其他大学提供。这种教育培训方法使新的实践社区能够有效地参与 HPC，并揭示了一种改善女性在超级计算中代表性不足的方法。