Nanosystems Engineers
Architecture and Engineering Occupations- رمز O*NET-SOC
- 17-2199.09
Design, develop, or supervise the production of materials, devices, or systems of unique molecular or macromolecular composition, applying principles of nanoscale physics and electrical, chemical, or biological engineering.
تُعرض أسماء المهن وأوصاف المهام بالإنجليزية كما نُشرت. أما التسميات، ومنها أنواع المهام، فمترجمة.
التعرّض للذكاء الاصطناعي
- مصدر البيانات: BLSتاريخ النشر: 2026-08
مرتفع جدًا· نسبي
منخفضأربع فئات نسبيةمرتفع جدًاقيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
أربع فئات نسبية (منخفض / متوسط / مرتفع / مرتفع جدًا)
831 مهنة تفصيلية في جدول توقعات التوظيف لدى BLS. وتُسند القيمة على مستوى رمز مصفوفة التوظيف الوطنية (NEM)، فالمهن التي تشترك في الرمز نفسه تأخذ النطاق نفسه
- مصدر البيانات: Anthropicتاريخ النشر: 2026-03
0.066
0.000نطاق القيم المعروضة هنا0.745قيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
مؤشر التعرّض المرصود، 0–1 كما نُشر
مربوط بمهام O*NET
منشورة لكل مهنة في SOC 2018؛ وكل مهنة في O*NET تحمل رمز SOC 2018 نفسه تأخذ هذه القيمة
- مصدر البيانات: ILOتاريخ النشر: 2025
0.30
0.09نطاق القيم المعروضة هنا0.70قيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
مؤشر التعرّض للذكاء الاصطناعي التوليدي، 0–1 كما نُشر
قيمة منشورة على مستوى مجموعة الوحدة في ISCO-08. رُبطت بهذه المهنة بتطبيق جداول التناظر الرسمية لمكتب إحصاءات العمل الأمريكي (BLS) (من ISCO-08 إلى SOC 2010، ومن SOC 2010 إلى SOC 2018) كما نُشرت، والتناظر كلي أو جزئي
ما نوع القيمة التي ينشرها هذا المصدر
فئة BLS رتبة نسبية لا مستوى مطلق، وليست قياسًا مباشرًا: فهي تجمع الرتب المئينية للمهنة في عدة دراسات منشورة في أربع فئات. وهي ليست توقّعًا للتوظيف أو الأجور، ولا احتمالًا للتبني، ولا تفرّق بين الأتمتة والتعزيز.
التعرض للذكاء الاصطناعي (معيار OpenAI)
25 مهمة مقيَّمة · 23 مهمة بقيمة β ≥ 0.5 (92.0%)
β = التعرّض المباشر (E1) + 0.5 × التعرّض عند توفر الأدوات (E2)، وفق تعريف المستودع المصدري.
- وحدة المصدر: مهام O*NET 27.2 ← رمز المهنة في O*NET 31.0
- جميع المهام المقيَّمة موجودة في قائمة مهام O*NET 31.0.
- المصدر
- OpenAI "GPTs are GPTs" exposure rubric
- الإصدار
- gh-main-0471612
- الترخيص
- MIT License, Copyright (c) 2024 OpenAI
المهام
أوصاف المهام من O*NET® 31.0 Database، والمهام الأساسية أولًا.
| المهمة | النوع | β (OpenAI) |
|---|---|---|
| Write proposals to secure external funding or to partner with other companies. | أساسية | 1 |
| Supervise technologists or technicians engaged in nanotechnology research or production. | أساسية | 0.5 |
| Synthesize, process, or characterize nanomaterials, using advanced tools or techniques. | أساسية | 0 |
| Identify new applications for existing nanotechnologies. | أساسية | 0.5 |
| Provide technical guidance or support to customers on topics such as nanosystem start-up, maintenance, or use. | أساسية | 0.5 |
| Generate high-resolution images or measure force-distance curves, using techniques such as atomic force microscopy. | أساسية | 0.5 |
| Prepare reports, deliver presentations, or participate in program review activities to communicate engineering results or recommendations. | أساسية | 1 |
| Develop processes or identify equipment needed for pilot or commercial nanoscale scale production. | أساسية | 0.5 |
| Provide scientific or technical guidance or expertise to scientists, engineers, technologists, technicians, or others, using knowledge of chemical, analytical, or biological processes as applied to micro and nanoscale systems. | أساسية | 0.5 |
| Engineer production processes for specific nanotechnology applications, such as electroplating, nanofabrication, or epoxy. | أساسية | 0 |
| Design or conduct tests of new nanotechnology products, processes, or systems. | أساسية | 0.5 |
| Coordinate or supervise the work of suppliers or vendors in the designing, building, or testing of nanosystem devices, such as lenses or probes. | أساسية | 0.5 |
| Design or engineer nanomaterials, nanodevices, nano-enabled products, or nanosystems, using three-dimensional computer-aided design (CAD) software. | أساسية | 0.5 |
| Create designs or prototypes for nanosystem applications, such as biomedical delivery systems or atomic force microscopes. | أساسية | 0.5 |
| Conduct research related to a range of nanotechnology topics, such as packaging, heat transfer, fluorescence detection, nanoparticle dispersion, hybrid systems, liquid systems, nanocomposites, nanofabrication, optoelectronics, or nanolithography. | أساسية | 1 |
| Apply nanotechnology to improve the performance or reduce the environmental impact of energy products, such as fuel cells or solar cells. | أساسية | 0.5 |
| Design nano-enabled products with reduced toxicity, increased durability, or improved energy efficiency. | أساسية | 0.5 |
| Prepare nanotechnology-related invention disclosures or patent applications. | تكميلية | 1 |
| Design nano-based manufacturing processes to minimize water, chemical, or energy use, as well as to reduce waste production. | تكميلية | 0.5 |
| Design nanoparticle catalysts to detect or remove chemical or other pollutants from water, soil, or air. | تكميلية | 0.5 |
| Design nanosystems with components such as nanocatalysts or nanofiltration devices to clean specific pollutants from hazardous waste sites. | تكميلية | 0.5 |
| Develop catalysis or other green chemistry methods to synthesize nanomaterials, such as nanotubes, nanocrystals, nanorods, or nanowires. | تكميلية | 1 |
| Develop green building nanocoatings, such as self-cleaning, anti-stain, depolluting, anti-fogging, anti-icing, antimicrobial, moisture-resistant, or ultraviolet protectant coatings. | تكميلية | 1 |
| Integrate nanotechnology with antimicrobial properties into products, such as household or medical appliances, to reduce the development of bacteria or other microbes. | تكميلية | 0.5 |
| Reengineer nanomaterials to improve biodegradability. | تكميلية | 1 |
معلومات مهنية
المصادر والإسناد
This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.
Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.
O*NET OnLine: 17-2199.09 Nanosystems Engineers
KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.