Rejobs

毕业实习生 - AI/ML 网络安全方向

加入美国Golden的National Laboratory of the Rockies,担任毕业实习生 - AI/ML 网络安全。此职位专注于提升电网安全的AI工具,强调可解释性和不确定性。享受医疗保险和403(b)储蓄计划等福利。

混合 实习 UTC-06:00 2 天前更新
薪资
US$51,200–81,900 /年

在 nrel.wd5.myworkdayjobs.com 申请

检查您的收件箱。

用手机?稍后可以在电脑上申请。

Posting Title

Graduate (10-12 weeks) Intern - AI/ML for Cybersecurity.

Location

CO - Golden.

Position Type

Intern (Fixed Term).

Hours Per Week

Job Description

The intern will conduct hands-on research at the intersection of machine learning, statistics, and critical energy infrastructure security. The position focuses on enhancing the reliability, transparency, and operator-readiness of AI-driven cybersecurity tools used to secure power grid substations and physical assets, with a primary focus on explainability and robust uncertainty bounds.

* Explainable AI (XAI): Design and implement XAI methods (e.g., attribution maps, rule extraction, root-cause analyses) to make complex ML models transparent and auditable for control-room operators and system administrators.

* Confidence & Uncertainty Quantification: Apply statistical techniques and frameworks (e.g., conformal prediction, Bayesian neural networks, or ensemble methods) to quantify model confidence and measure predictive uncertainty in real-time.

* Grid Dataset Analysis: Analyze cyber-physical power system security datasets (such as 9-Bus system baseline and cyber-physical anomaly runs) to extract feature patterns and validate anomaly detection model behavior.

* Model Safety & Robustness: Explore machine learning safety techniques, including model steering, to ensure grid security models behave predictably under distribution shifts or input corruptions.

* Visualization & Alert Design: Support research into visualization methods and alert design that present explainability and confidence metrics clearly to operators, assisting with alert prioritization.

* Collaboration & Reporting: Partner with cybersecurity researchers and AI development teams to integrate explainability modules, document results, and compile guidelines for deploying reliable AI models.

.

Basic Qualifications

Minimum of a 3.0 cumulative grade point average.

Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution.
Post Undergraduate: Earned a bachelor's degree within the past 12 months. Eligible for an internship period of up to one year.

Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution.
Post Graduate: Earned a master's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution.

Please Note

* Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
* If selected for position, a letter of recommendation will be required as part of the hiring process.
* Must meet educational requirements prior to employment start date.* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

* Education: Currently pursuing or completed a Bachelor's, Master's, or Ph.D. in Computer Science, Cybersecurity, Electrical Engineering, AI, Applied Mathematics, or Statistics.

* Programming & ML Frameworks: Strong proficiency in Python; hands-on experience with PyTorch, TensorFlow, or Hugging Face.

* Core Research Competency: Substantial coursework or project experience in Explainable AI (XAI), machine learning safety, confidence calibration, or statistical uncertainty modeling.

* Generative AI / LLMs: Practical experience working with Large Language Models (LLMs) or Foundation Models or other complex deep neural networks.

Preferred Qualifications

* Active research/publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, AAAI, IEEE S&P, USENIX Security, or ACM CCS) with a focus on XAI, robust ML, or cyber-physical energy systems.

* Experience with specialized explainability libraries (such as Captum, SHAP, or LIME) and uncertainty calibration methods.

* Familiarity with multi-sensor data fusion, power systems modeling, or grid anomaly detection.

* Contributions to open-source software libraries focusing on AI transparency, reliability, or security.

.

Job Application Submission Window

Annual Salary Range (based on full-time 40 hours per week)

Job Profile: Graduate / Annual Salary Range: $51,200 - $81,900NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.

Benefits Summary

Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.* Based on eligibility rules

Badging Requirement

NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.# Drug Free Workplace

NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.

If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.

Submission Guidelines

Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.

.

Equal Opportunity Employer

All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

Reasonable Accommodations

E**-Verify [www.dhs.gov/E-Verify**](http://www.dhs.gov/E-Verify) For information about right to work, click here for English or here for Spanish.

E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.

薪资与福利

US$51,200–81,900 /年
医疗保险 牙科保险 视力保险 退休计划 带薪休假

职位详情

发布时间
28 10月 2026
更新时间
28 10月 2026
工作类型
实习
工作地点
混合
领域
工作时间
UTC-06:00
经验
入门级

关于 National Laboratory of the Rockies

公司概况

名称

落基山国家实验室,美国能源部直属国家实验室

总部

美国科罗拉多州戈尔登市

成立时间

1977年

规模

约3700名员工,包括工作人员、博士后研究员、实习生、访问专家及分包商(来源:wikipedia.org)

业务范围

落基山国家实验室是一家联邦资助的研究机构,专注于涵盖整个能源系统的应用能源研发,包括发电、分配及终端使用(来源:nlr.gov)。其研究领域广泛,涵盖太阳能、风能、可再生燃料、车辆系统、建筑、地热、能源科学、计算科学及能源分析等多种能源技术(来源:nationallabs.org)。实验室还设有多个专业中心,包括国家光伏中心、国家生物能源中心和国家风能技术中心,支持各自领域的重点研究与创新(来源:wikipedia.org)。作为能源部的国家实验室,它在联邦合同框架下运营,为公共部门和产业合作伙伴开发技术,降低新兴能源系统的风险(来源:nlr.gov)。

项目与业绩

实验室拥有丰富的项目经验,包括开发SEA-Stack波浪能技术筛选与设计工具,帮助企业快速评估概念,降低海洋能源创新的时间和成本(来源:nlr.gov)。此外,支持BOTTLE联盟的化学氧化回收平台,旨在实现受污染、混合及多层塑料废料的可规模化处理,解决可持续材料管理中的关键难题(来源:nlr.gov)。落基山国家实验室运营科罗拉多的国家风能技术中心,这是推动风能技术发展的重要设施,并在华盛顿特区设有办事处,支持政策制定和利益相关者沟通(来源:nlr.gov)。这些项目体现了实验室在可再生能源研究领域的领导地位及其加速全国清洁能源解决方案的承诺。

最新动态

2025年12月,能源部正式将国家可再生能源实验室更名为落基山国家实验室,以体现其不断发展的使命和区域特色(来源:nlr.gov)。2025年至2026年间,实验室持续活跃于先进能源研究,发布了海洋及波浪能技术、塑料回收创新及量子相关材料研究的进展(来源:nlr.gov)。然而,实验室也经历了人员调整,2026年2月裁员134人,此前2025年5月已裁员至少114人,反映出在资金和项目优先级变化下的组织调整(来源:cpr.org)。

工作环境

落基山国家实验室提供涵盖研究、软件与计算科学、实验室运营、工程、项目管理、传播及行政支持等多样化岗位,均在联邦资助的研发环境中开展(来源:techjobsforgood.com)。员工享有全面的医疗、牙科和视力保险,403(b)退休储蓄计划及雇主配比,养老金资格,残疾保险,学费报销及职业发展机会(来源:nlr.gov)。位于科罗拉多州戈尔登的园区配备健身中心、餐厅、咖啡厅、会议空间及开放式步道,营造协作且灵活的工作文化,支持早期职业发展与工作生活平衡(来源:nlr.gov)。

您的 LinkedIn 人脉

在 LinkedIn 上查看您在 National Laboratory of the Rockies 的联系人,申请时善用您的人脉。

查看人脉

更多 智能电网 相似职位

毕业实习生 - AI/ML 网络安全方向
National Laboratory of the Rockies · US$51,200–81,900/年