An investigation into the application of machine learning algorithms for the discrimination, classification and optimal application of a military (nuc

该提案旨在研究如何将机器学习技术用作核导弹防御系统的一部分。结合候选雇主AWE的知识，AWE是负责英国的组织。的核武器计划，与国防和机器学习专家在学术界。由于涉及核武器的影响和对核武器影响的反应，这将不同于先前的研究，这是原子武器博览会特别感兴趣的一个领域。该项目的目标可概括如下。首先，研究能够正确区分和分类威胁和核设备的机器学习算法，然后在核环境中运行时，通过最佳使用其资产来响应检测到的场景。其次，培养候选人在机器学习技术方面的技能，以便能够将其应用于未来的其他工作领域。最后，培训候选人在许多所需领域（如雷达系统）的专业知识水平。预计结果将是相关的高标准文件的调查结果，代表性的计算模型和主题的专业知识，以候选人。

The proposal is to investigate how machine learning techniques can be used as part of a nuclear missile defence system. Combining the knowledge of the candidate employer AWE, the organisation responsible for the U.K.'s nuclear weapons programme, with defence and machine learning experts in academia. This will differ from pre-existing research due to the involvement and response to nuclear weapon effects, an area of specific interest to AWE. The objectives of the project can be summarised as follows. Firstly, to investigate machine learning algorithms that can correctly discriminate and classify threats and nuclear devices, then respond to the scenario detected with optimal usage of its assets, while operating around nuclear environments. Secondly, develop the candidate's skillset in machine learning techniques to then be able to apply them to additional future areas of work. Finally, to train the candidate to a competent level of expertise in many of the required fields (such as radar systems). The outcomes are expected to be the relevant high standard documentation of findings, representative computational models and subject matter expertise to the candidate.