Bioengineers and Biomedical Engineers

Architecture and Engineering Occupations
رمز O*NET-SOC
17-2031.00

Apply knowledge of engineering, biology, chemistry, computer science, and biomechanical principles to the design, development, and evaluation of biological, agricultural, and health systems and products, such as artificial organs, prostheses, instrumentation, medical information systems, and health management and care delivery systems.

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 جدًا

    قيمة 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

    مجموعة البيانات المصدر (تنزيل ملف XLSX)

  • مصدر البيانات: Anthropicتاريخ النشر: 2026-03

    0.133

    0.000نطاق القيم المعروضة هنا0.745
    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

    مجموعة البيانات المصدر (تنزيل ملف CSV)

  • مصدر البيانات: ILOتاريخ النشر: 2025

    0.30

    0.09نطاق القيم المعروضة هنا0.70

    قيمة 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

    مجموعة البيانات المصدر (تنزيل ملف PDF)

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)

30 مهمة مقيَّمة · 29 مهمة بقيمة β ≥ 0.5 (96.7%)

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.

المهمةالنوعβ (OpenAI)
Evaluate the safety, efficiency, and effectiveness of biomedical equipment.أساسية0.5
Advise hospital administrators on the planning, acquisition, and use of medical equipment.أساسية0.5
Research new materials to be used for products, such as implanted artificial organs.أساسية0.5
Develop models or computer simulations of human biobehavioral systems to obtain data for measuring or controlling life processes.أساسية0.5
Conduct research, along with life scientists, chemists, and medical scientists, on the engineering aspects of the biological systems of humans and animals.أساسية0.5
Adapt or design computer hardware or software for medical science uses.أساسية1
Conduct training or in-services to educate clinicians and other personnel on proper use of equipment.أساسية0
Write documents describing protocols, policies, standards for use, maintenance, and repair of medical equipment.أساسية1
Collaborate with manufacturing or quality assurance staff to prepare product specification or safety sheets, standard operating procedures, user manuals, or qualification and validation reports.أساسية1
Communicate with bioregulatory authorities regarding licensing or compliance responsibilities.أساسية0.5
Communicate with suppliers regarding the design or specifications of bioproduction equipment, instrumentation, or materials.أساسية0.5
Confer with research and biomanufacturing personnel to ensure the compatibility of design and production.أساسية0.5
Consult with chemists or biologists to develop or evaluate novel technologies.أساسية0.5
Design or conduct follow-up experimentation, based on generated data, to meet established process objectives.أساسية0.5
Design or develop medical diagnostic or clinical instrumentation, equipment, or procedures, using the principles of engineering and biobehavioral sciences.أساسية1
Develop methodologies for transferring procedures or biological processes from laboratories to commercial-scale manufacturing production.أساسية0.5
Develop statistical models or simulations, using statistical or modeling software.أساسية1
Maintain databases of experiment characteristics or results.أساسية1
Manage teams of engineers by creating schedules, tracking inventory, creating or using budgets, or overseeing contract obligations or deadlines.أساسية0.5
Prepare project plans for equipment or facility improvements, including time lines, budgetary estimates, or capital spending requests.أساسية0.5
Prepare technical reports, data summary documents, or research articles for scientific publication, regulatory submissions, or patent applications.أساسية1
Read current scientific or trade literature to stay abreast of scientific, industrial, or technological advances.أساسية0.5
Recommend process formulas, instrumentation, or equipment specifications, based on results of bench or pilot experimentation.أساسية0.5
Analyze new medical procedures to forecast likely outcomes.تكميلية0.5
Advise manufacturing staff regarding problems with fermentation, filtration, or other bioproduction processes.تكميلية0.5
Design and deliver technology, such as prosthetic devices, to assist people with disabilities.تكميلية0.5
Design or direct bench or pilot production experiments to determine the scale of production methods that optimize product yield and minimize production costs.تكميلية0.5
Develop bioremediation processes to reduce pollution, protect the environment, or treat waste products.تكميلية0.5
Lead studies to examine or recommend changes in process sequences or operation protocols.تكميلية0.5
Review existing manufacturing processes to identify opportunities for yield improvement or reduced process variation.تكميلية0.5

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: 17-2031.00 Bioengineers and Biomedical 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.

الإسناد والتراخيص كاملة