how_to_write_an_application_letter_in_english

新网编辑教育资讯 2025-12-25 17

一、什么是申请信？它到底写给谁？

申请信（Application Letter）是一封正式书信，用来向学校、公司或机构表达“我想加入”的意愿。它通常写给招生官、人力资源经理或项目负责人，目的是让对方在几十秒内决定“这个人值得面试”。

how_to_write_an_application_letter_in_english-第1张图片-星辰妙记

（图片来源网络，侵删）

二、写之前必须自问自答的三个关键问题

我是谁？——用一句话概括身份，例如“我是一名即将毕业的计算机科学硕士”。
我为什么申请？——用两句话说明动机，例如“贵公司的AI实验室在NLP领域领先，我的毕业设计正是情感分析”。
我能带来什么？——用三个成就证明价值，例如“发表两篇SCI论文、带队赢得Kaggle银牌、实习期间将模型准确率提升12%”。

三、黄金结构：四段式模板拆解

1. 开头段：三行钩子

第一行直接点名职位或项目：“I am writing to apply for the Research Assistant position advertised on your website.”
第二行建立连接：“My academic background in machine learning aligns seamlessly with your team’s focus on multilingual sentiment analysis.”
第三行抛出亮点：“During my master’s, I developed a BERT-based model that outperformed the state-of-the-art by 3.7%.”

2. 主体段一：学术或职业成就

用“情境-行动-结果”公式写两个例子：
情境：课程项目需要处理20万条多语言评论。
行动：我设计数据清洗脚本并微调XLM-R。
结果：F1-score从0.82提升到0.897，代码开源后获GitHub 500+ stars。

3. 主体段二：软技能与文化契合

列举三点并给出证据：
• 跨文化沟通：作为交换生在德国实验室用英语、德语协调三国团队。
• 领导力：带领五人小组在48小时黑客松中开发抑郁症检测App并夺冠。
• 持续学习：每周阅读arXiv最新论文并做团队分享，已坚持两年。

4. 结尾段：行动号召

用一句礼貌而自信的请求：“I would welcome the opportunity to discuss how my research experience can contribute to your upcoming multilingual project.”
附上可联系时间：“I am available for an interview any weekday after 2 p.m. CET.”

四、语言细节：让招生官眼前一亮的五个技巧

动词优先：用“engineered”“optimized”“spearheaded”替换“did”“made”。
量化结果：把“improved efficiency”写成“cut inference time from 200 ms to 47 ms”。
避免空洞形容词：删掉“hard-working”，用事实体现。
一行一句：屏幕阅读时代，长段等于劝退。
统一时态：过去经历用一般过去时，当前职责用现在时。

五、常见错误自查清单

错误类型	案例	修改建议
拼写公司名	“MicroSoft”	官网复制粘贴
重复简历	“As shown in my CV...”	用故事补充，而非复述
过度谦卑	“I know I may not be the best...”	删除，保持自信

六、实战范例：申请数据科学实习

Dear Dr. Schmidt,

I am writing to express my interest in the Data Science Internship at XYZ GmbH, as advertised on LinkedIn. Having spent the last year optimizing transformer models for low-resource languages, I am eager to apply this expertise to your Swahili voice assistant project.

At RWTH Aachen, I led a team of four to fine-tune Whisper-small on 120 hours of East African radio recordings. By implementing dynamic batching and gradient checkpointing, we reduced training time by 38% while maintaining a WER of 18.4%, outperforming Google’s baseline by 5.1 points. Our dataset and code are publicly available and have already been forked 210 times.

Beyond technical depth, I bring startup agility. Last summer, I interned at a Berlin health-tech firm where I deployed an on-device cough detection model to 50,000 Android users within eight weeks. Collaborating with product managers in daily stand-ups taught me to translate research metrics into user-centric KPIs.

I would be thrilled to discuss how my experience with multilingual ASR can accelerate XYZ’s mission of inclusive AI. I am available for a call any weekday after 10 a.m. CET.

Thank you for your time and consideration.

Sincerely,
Li Hua
li.hua@email.com
+49 151 2345 6789