Learn to Discover (L2D): A Training Platform in Data Sciences and Machine Learning for Biomedicine and Health Researchers.

数字技能需要提高，以优化数字技术加速应用带来的竞争潜力。生物和医学科学正在变得更加自动化，以解决发现和应用健康和医学科学中更大、更复杂的问题。常规采用全新的工作方式并优化其在这一关键领域的影响的必要性只会增加。我们需要采取行动，不断提高英国科学工作者的技能，因为数字技能的部署提供了非常强劲的增长机会。英国政府致力于技术的未来和能够带来经济增长的部门，并从其他地方吸取了经验教训：过去50年美国经济增长的50%来自STEM学科中5%的劳动力。将数字技术技能的采用融合到发现生物科学、生物医学和健康科学等高价值的STEM学科中，英国已经在这些领域发挥了很大的作用，具有巨大的潜力，可以产生有意义的、可衡量的经济和社会影响。然而，解决数字技能危机不是一件小事。英国长期的供应问题需要激进的行动。作为一名数据专家，需要了解数学、编码和计算机科学，以及解决问题、应变能力和沟通能力。”（英国皇家学会：2019年5月）。2011年起，SysMIC (http://sysmic.ac。英国)——最初由BBSRC资助——利用数字技术、互联网接入和大多数专业人员广泛可用的远程通信基础设施，在活跃的生物科学和健康研究人员中解决了这一技能问题的一半。我们在数学、计算和统计方法方面提供高质量的电子学习和培训。“学习2发现”（L2D）项目将把面向健康和生物科学的领先计算和数据科学家的专业知识与SysMIC的远程学习敏敏性和资源相结合，以解决剩下的部分挑战。L2D我们将提供数据科学、机器学习和人工智能培训，以一种高度可访问的、灵活的、模块化的形式，适合各种各样的初学者（包括初学者）和学习制度。我们的模块将借鉴已建立的现实世界的例子，但提供广泛适用的技能和一般的计算自信，有效地应用远远超出课程。通过网络交付提供了对高等教育系统中断的弹性，并利用了2020年在研发人员中开发的远程工作和学习能力。英国生物产业利益相关者参与该计划的设计，将促进学术和商业部门之间的人才流动和共享。我们的模块与英国卓越研究中心、基础设施和资源网络的合作和协调将提高知名度、信心和需求。L2D将直接解决数字生产力难题，促进知识交流，并将其转化为对社会和经济的影响，并将为跨部门的培训效益溢出提供机会。未能有效应对数字技能挑战是企业增长、创新和更广泛的社会发展面临的主要风险。在英国劳动力市场上，合适的数字技能的短缺仍然存在——研究生物医学和健康科学并不是一个孤立的案例。对具有专业数据科学和计算技能的员工的需求增长速度是其他所有需求的6.5倍。最好的选择是在本地培养生物、生物医学和健康研究领域的人才，并提供第二级持续专业进修。持续的数字技能工资差异使得有影响力的、广泛的数字技能培训具有吸引力，并且物有所值，因为超过75%的任何技能级别的职位空缺都要求数字技能。

Digital skills need to improve to optimise competitive potential from accelerating applications of digital technology. Biological and medical science is becoming more automated to tackle bigger and more complex problems in discovery and applied health and medical sciences. The need for routine adoption of radically new ways of working and optimisation of their impact in this critical sector will only increase. We need action to re-skill the UK scientific workforce continuously since the deployment of digital skills offers very strong growth opportunities. The UK Government has committed to a technological future and to sectors that can deliver economic growth and has learnt lessons from elsewhere: 50% of all growth in the US economy over the last 50 years has come from the 5% of the workforce in STEM disciplines. Fusing the adoption of digital tech skills to the especially high-value STEM disciplines of discovery bioscience, biomedical and health sciences, where the UK already punches well above its weight, has tremendous potential for meaningful and measurable economic and social impact. However, tackling a digital skills crisis is not a trivial undertaking "Britain's chronic supply issues requires radical action. Working as a data expert requires knowing your maths, coding and computer science as well as problem solving, resilience and communication." (The Royal Society: - May 2019). Since 2011 SysMIC (http://sysmic.ac.uk) - funded initially by the BBSRC - has taken advantage of the digital technology, internet access, and distant communication infrastructure widely available for most professionals to address half of this skills problem amongst active bioscience and health researchers. We delivered high-quality, e-learning and training in mathematical, computational and statistical methods. The Learn 2 Discover (L2D) project will combine the expertise of leading health and bioscience-facing computational and data scientists with the remote learning acumen and resources of SysMIC to solve the remaining part of the challenge. L2D we will deliver data science, machine learning and AI training in a highly accessible, flexible, modular format, suitable for a very wide range of starting expertise - including beginners - and study regimes. Our modules will draw on established real-world examples yet deliver widely applicable skills and general computational self-confidence for effective application well beyond the course. Delivery through the web offers resilience to disruptions of HE systems and leverages remote work and study competence developed across the R&D workforce in 2020 Participation of UK bioindustry stakeholders in the design of the programme will promote movement and sharing of talent between academic and commercial sectors. Collaboration and alignment of our modules with the work of UK centres of research excellence, infrastructure and resource networks will promote visibility, confidence and demand. L2D will squarely address the digital productivity puzzle and promote knowledge exchange and its translation into impact in society and the economy and will offer opportunities for cross-sector spill over of benefits from training. Failure to respond effectively to the digital skills challenge is a major risk to business growth, innovation and broader societal development. A shortage in suitable digital skills persists in the UK labour market - research biomedical and health sciences is not an isolated case. Demand for workers with specialised data sciences and computational skills has been growing 6.5-fold faster than all other requirements. The best option is to nurture talent in the bio-, biomedical and health research sectors in situ with first class CPD of the sort proposed in L2D. A persistent digital skills wage differential makes impactful, broad digitals skills training attractive and very good value for money since over 75% of job openings at any skill level request digital skills.