Learning to match applicants to job profiles

拟议的研究活动将有助于提高将潜在求职者与招聘经理发布的寻找合适候选人的职位进行匹配的能力。这是一项基于机器学习、数据科学和神经网络的研究努力，旨在从数据中提取最大价值，并提供最佳匹配和招聘结果。拟议的研究将有助于基于大型和异质数据的决策，也提供新的能力和新方向的可扩展性，具有指数增长的潜力。考虑的数据范围从基于文本的候选人描述到更有针对性的措施，以告知填补工作的匹配质量。将应用人工智能和深度学习的现代进步，以及系统设计的谨慎原则，以提供最佳匹配和聘用后的成功结果。

The proposed research activities will help to improve capabilities in matching prospective job applicants tojobs posted by hiring managers seeking suitable candidates. This is a research endeavor grounded in machinelearning, data science and neural networks towards extracting maximum value from data, and providing bestpossible matches, and outcomes in hiring.The proposed research will help with decision making based on large and heterogeneous data, also providingnew capabilities, and scalability in new directions with potential for exponential growth. Data consideredranges from text based candidate descriptions to more targeted measures that inform on quality of fit in fillingjobs.Modern advances in AI and deep learning will be applied, alongside careful principles of system design toprovide optimal matches, and successful outcomes post-hire.