Biofuels/Biodiesel Technology and Product Development Managers
Management Occupations- رمز O*NET-SOC
- 11-9041.01
Define, plan, or execute biofuels/biodiesel research programs that evaluate alternative feedstock and process technologies with near-term commercial potential.
تُعرض أسماء المهن وأوصاف المهام بالإنجليزية كما نُشرت. أما التسميات، ومنها أنواع المهام، فمترجمة.
التعرّض للذكاء الاصطناعي
- مصدر البيانات: BLSتاريخ النشر: 2026-08
مرتفع· 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
0.031
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
0.40
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)
19 مهمة مقيَّمة · 14 مهمة بقيمة β ≥ 0.5 (73.7%)
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
- عدد المهام المقيَّمة غير الموجودة في قائمة مهام O*NET 31.0: 1؛ وتبقى درجاتها كما نُشرت وفق O*NET 27.2.
- 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) |
|---|---|---|
| Develop lab scale models of industrial scale processes, such as fermentation. | أساسية | 0 |
| Provide technical or scientific guidance to technical staff in the conduct of biofuels research or development. | أساسية | 0.5 |
| Prepare, or oversee the preparation of, experimental plans for biofuels research or development. | أساسية | 0.5 |
| Prepare biofuels research and development reports for senior management or technical professionals. | أساسية | 0.5 |
| Design or conduct applied biodiesel or biofuels research projects on topics, such as transport, thermodynamics, mixing, filtration, distillation, fermentation, extraction, and separation. | أساسية | 0.5 |
| Conduct experiments on biomass or pretreatment technologies. | أساسية | 0 |
| Conduct experiments to test new or alternate feedstock fermentation processes. | أساسية | 0 |
| Analyze data from biofuels studies, such as fluid dynamics, water treatments, or solvent extraction and recovery processes. | أساسية | 0.5 |
| Oversee biodiesel/biofuels prototyping or development projects. | أساسية | 0.5 |
| Propose new biofuels products, processes, technologies or applications based on findings from applied biofuels or biomass research projects. | أساسية | 0.5 |
| Develop computational tools or approaches to improve biofuels research and development activities. | تكميلية | 1 |
| Perform protein functional analysis and engineering for processing of feedstock and creation of biofuels. | تكميلية | 0.5 |
| Develop separation processes to recover biofuels. | تكميلية | 0 |
| Develop methods to recover ethanol or other fuels from complex bioreactor liquid and gas streams. | تكميلية | 1 |
| Develop methods to estimate the efficiency of biomass pretreatments. | تكميلية | 0.5 |
| Design or execute solvent or product recovery experiments in laboratory or field settings. | تكميلية | 0 |
| Design chemical conversion processes, such as etherification, esterification, interesterification, transesterification, distillation, hydrogenation, oxidation or reduction of fats and oils, and vegetable oil refining. | تكميلية | 1 |
| Conduct research to breed or develop energy crops with improved biomass yield, environmental adaptability, pest resistance, production efficiency, bioprocessing characteristics, or reduced environmental impacts. | تكميلية | 0.5 |
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: 11-9041.01 Biofuels/Biodiesel Technology and Product Development Managers
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.