Adding AI-powered analysis capabilities to Lifelancer platform

为 Lifelancer 平台添加人工智能分析功能

• 批准号: 10089687
• 金额: $ 0.99万
• 依托单位: LIFELANCER LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10089687
• 关键词: Adding; AI; powered; analysis; capabilities

Labor markets & job boards around the world have not kept pace with rapid shifts in the global economy, and their inefficiencies take a heavy toll. Millions of people cannot find work, yet sectors from technology to health care cannot find people to fill open positions.For employers, traditional recruiting methods are expensive, slow, and outdated, and are not helping to connect them with the right talent swiftly. For talent, current methods (general job boards & online platforms) do not match them with job opportunities very well.AI-powered & domain-specific tech platforms have the potential to address the above inefficiencies in the labor markets and make the processes 50-100X faster, more efficient & accurate compared to the current tech. At present, there is no global tech platform addressing the above in the life sciences.**Lifelancer is building the first AI-powered platform for talent hiring & upskilling in the life sciences & related IT domains.** The project would focus on analyzing large-quality of text-based data, extracting relevant information, building scoring matrices & AI-ML modeling.The project will be done in collaboration with Digital Services group at TUV SUD National Engineering Laboratory (NEL). Digital Services group at NEL consists of highly experienced professionals, who actively work on developing, implementing, and benchmarking state-of-the-art machine learning algorithms to model & analyze large volumes of data. Supported by both world-class facilities and a state-of-the-art internal HPC cluster with over 600 cores, NEL has the computational power and technical expertise for the AI-powered analysis for the project.

全球劳动力市场和工作委员会并没有跟上全球经济的快速变化，他们的效率低下造成了巨大的损失。数以百万计的人找不到工作，但是从技术到医疗保健的部门找不到可以填补公开职位的人。对于雇主来说，传统的招聘方法是昂贵，缓慢且过时的，并且没有帮助他们迅速将其与合适的人才联系起来。对于人才，当前的方法（一般工作委员会和在线平台）与工作机会不佳。驱动和领域特定的技术平台有可能解决劳动力市场中上述低效率的问题，并且与当前技术相比，该流程更快，更有效，更准确。目前，没有全球技术平台来解决生命科学中的上述问题。实验室（NEL）。 NEL的数字服务小组由经验丰富的专业人士组成，他们积极致力于开发，实施和基准测试最先进的机器学习算法，以建模和分析大量数据。 NEL在世界一流的设施和拥有600多个内核的最先进的内部HPC群集的支持下，具有用于该项目的AI驱动分析的计算能力和技术专业知识。