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法国农业科学研究院生物质资源地理空间优化及决策支持平台开发博士后职位

  • 2026-03-29 13:45:12
法国农业科学研究院生物质资源地理空间优化及决策支持平台开发博士后职位

INRAE presentation

The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a major player in research and innovation. It is a community of 12,000 people with 272 research, experimental research, and support units located in 18 regional centres throughout France. Internationally, INRAE is among the top research organisations in the agricultural and food sciences, plant and animal sciences, as well as in ecology and environmental science. It is the world’s leading research organisation specialising in agriculture, food and the environment. INRAE’s goal is to be a key player in the transitions necessary to address major global challenges. Faced with a growing world population, climate change, resource scarcity, and declining biodiversity, the Institute has a major role to play in building solutions and supporting the necessary acceleration of agricultural, food and environmental transitions.

Work environment, missions and activities

You will be welcomed at BioEcoAgro (https://www.bioecoagro.eu/), based in Laon, France. The postdoctoral position is part of the Chaire de Professeur Junior (CPJ) research program led by Shule Wang at INRAE, which aims to develop an integrated territorial planning framework for future agricultural biomass mobilization and bioeconomy deployment. The project focuses primarily on agricultural biomass resources derived from crop modeling, in particular scenario-based outputs from agronomic models such as STICS, and seeks to connect these data with conversion pathway assessment, regional logistics, and decision-support tools for territorial and agricultural planning.

Your work will contribute to the development of a modular computational platform able to translate crop-model-derived biomass outputs into planning-relevant information. The platform will integrate spatially explicit agricultural biomass availability, pathway compatibility, transport and logistics constraints, and environmental, techno-economic, policy, and social considerations in order to support regional scenario exploration and optimization. Other biomass residue streams may be included as complementary inputs through existing external datasets, but the core of the project is future agricultural biomass and its role in regional planning.

The transition towards a sustainable and climate-oriented bioeconomy requires not only reliable projections of future agricultural biomass quantity, type, location, and temporal availability, but also robust methods to evaluate how these resources can be mobilized and allocated across competing end uses under realistic constraints. The postdoctoral researcher will therefore lead the computational integration and platform development aspects of the project, in close interaction with a PhD project dedicated to the detailed methodological development of key planning components.

You will be in charge of:

  • Developing a modular computational platform for territorial planning based on crop-model-derived agricultural biomass datasets; 

  • Integrating and harmonizing agronomic, spatial, logistical, and pathway-related datasets using Python and GIS-based workflows; 

  • Supporting the modeling integration of a PhD project by connecting its methodological components within the overall computational framework; 

  • Designing and implementing optimization models for biomass allocation, supply chain configuration, and regional scenario analysis, using approaches including but not limited to MILP and MINLP depending on the requirements of the final framework; 

  • Contributing to the representation and integration of environmental, techno-economic, policy, and social constraints within the decision-support framework; 

  • Contributing to scientific publications, project reports, and presentations at national and international meetings. 

Supervision: Shule Wang (INRAE, BioEcoAgro). The postdoctoral researcher will work in close interaction with colleagues and collaborators involved in agronomic systems modeling, spatial analysis, sustainability assessment, and territorial bioeconomy research within BioEcoAgro and partner institutions. Received applications will be reviewed on a rolling basis, and candidates are encouraged to apply early, as administrative procedures for the selected candidate may require additional lead time prior to the planned start date.

Training and skills

PhD

The applicant should hold a PhD in a relevant field, including but not limited to agricultural systems modeling, agricultural engineering, geoinformatics, spatial analysis, environmental systems engineering, operations research, bioeconomy systems analysis, or related disciplines. The candidate should demonstrate strong quantitative and computational skills, with experience in Python programming, spatial data processing/GIS, and model integration. Experience in optimization methods, such as MILP, MINLP, Gurobi, or related approaches, is highly desirable. Familiarity with agricultural systems, crop modeling outputs, biomass resource assessment, biomass conversion technologies, LCA/TEA or territorial planning would be considered an advantage. The applicant is expected to show a strong capacity for independent research, innovative thinking, and interdisciplinary collaboration. Excellent written and spoken English is required. French would be appreciated but is not mandatory.

Assessment criteria:

· The scientific quality and relevance of the candidate’s academic background and previous research experience; 

· The candidate’s quantitative and computational skills, especially in Python, GIS-based spatial data processing, and model integration; 

· Previous experience in optimization and territorial or resource allocation modeling, including approaches such as MILP, MINLP, Gurobi, or related methods; 

· The candidate’s capacity to work across disciplines at the interface of agricultural systems, biomass planning, logistics, and sustainability assessment; 

· Evidence of autonomy, innovative thinking, and the ability to contribute to the development of original scientific methods and publications; 

· The ability to collaborate within an interdisciplinary project and to contribute to the integration of modeling activities across the overall framework; 

·  Communication skills in English, both written and oral.

INRAE's life quality

By joining our teams, you benefit from (depending on the type of contract and its duration):

- up to 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);parenting support: CESU childcare, leisure services;- skills development systems: trainingcareer advise;social support: advice and listening, social assistance and loans;holiday and leisure services: holiday vouchers, accommodation at preferential rates;sports and cultural activities;- collective catering.

具体内容和申请方式可以点击阅读原文查看。

小编的网页翻译版:

INRAE介绍

法国国家农业、食品与环境研究所(INRAE)是科研与创新的重要参与者。这是一个拥有12,000人口的社区,拥有272个研究、实验研究和支持单位,分布在法国18个区域中心。在国际上,INRAE是农业与食品科学、植物与动物科学,以及生态学和环境科学领域的顶尖研究机构之一。它是全球领先的农业、食品与环境研究机构。INRAE的目标是成为应对重大全球挑战转型的关键角色。面对全球人口增长、气候变化、资源稀缺和生物多样性下降,研究所在构建解决方案和支持必要加速农业、食品和环境转型方面发挥着重要作用。

工作环境、使命与活动

您将在总部位于法国拉昂的BioEcoAgro(https://www.bioecoagro.eu/)受到欢迎。该博士后职位是INRAE由王修乐领导的初级教授(CPJ)研究项目的一部分,旨在为未来农业生物质动员和生物经济部署建立综合的地域规划框架。该项目主要聚焦于作物建模中提取的农业生物质资源,特别是基于情景的农学模型(如STICS)产出,并试图将这些数据与转化路径评估、区域物流以及地域和农业规划的决策支持工具相结合。

您的工作将有助于开发一个模块化计算平台,将作物模型衍生的生物质产出转化为规划相关信息。该平台将整合空间明确的农业生物质可用性、路径兼容性、运输与物流限制,以及环境、技术经济、政策和社会考量,以支持区域情景的探索与优化。其他生物质残留流可通过现有外部数据集作为补充投入纳入,但项目核心是未来农业生物质及其在区域规划中的作用。

向可持续且气候导向的生物经济转型不仅需要对未来农业生物质数量、类型、地点和时间可用性的可靠预测,还需要有力的方法来评估这些资源如何在现实约束下被动员和分配到竞争的终端用途之间。博士后研究员将负责项目的计算集成和平台开发,并与专注于关键规划组成部分详细方法论开发的博士项目密切合作。

你将负责:

  • 基于作物模型衍生的农业生物质数据集开发模块化的领土规划计算平台;

  • 利用基于Python和GIS的工作流程整合并协调农学、空间、物流及路径相关数据集;

  • 通过将博士项目的方法论组成部分在整体计算框架内连接,支持建模集成;

  • 设计和实施生物质分配、供应链配置和区域情景分析的优化模型,采用包括但不限于MILP和MINLP等方法,具体取决于最终框架的要求;

  • 促进环境、技术经济、政策和社会约束在决策支持框架中的代表性和整合;

  • 参与科学出版物、项目报告及国内外会议报告。

指导:Shule Wang(INRAE,BioEcoAgro)。博士后研究人员将与参与农学系统建模、空间分析、可持续性评估及BioEcoAgro及其合作机构领土生物经济研究的同事和合作者密切合作。收到的申请将以滚动方式审核,鼓励候选人尽早申请,因为入选候选人的行政程序可能需要在计划开始前额外提前时间。

培训与技能

博士学位

申请人应拥有相关领域的博士学位,包括但不限于农业系统建模、农业工程、地理信息学、空间分析、环境系统工程、运筹学、生物经济系统分析或相关学科。候选人应具备强大的定量和计算能力,具备Python编程、空间数据处理/GIS及模型集成经验。具备优化方法经验者,如MILP、MINLP、Gurobi或相关方法,尤为理想。熟悉农业系统、作物建模产出、生物质资源评估、生物质转化技术、LCA/TEA或领土规划将被视为优势。申请人需展现出强大的独立研究能力、创新思维和跨学科合作能力。要求具备优秀的书面和口语英语能力。法语会很受欢迎,但不是强制的。

评估标准:

·候选人的学术背景和以往研究经验的科学质量和相关性;

·候选人的定量和计算能力,特别是Python、基于GIS的空间数据处理和模型集成;

·具备优化及领土或资源分配建模经验,包括MILP、MINLP、Gurobi等方法;

·候选人具备跨学科合作的能力,涵盖农业系统、生物质规划、物流及可持续性评估;

·展现自主性、创新思维以及为原创科学方法和出版物发展做出贡献的能力;

·能够在跨学科项目中协作,并促进建模活动在整体框架内的整合;

·英语沟通能力,包括书面和口头。

INRAE的生活质量

加入我们的团队,您将享受(取决于合同类型及其期限):

- 最多30天年假+15天“减少工作时间”(全职);- 育儿支持:CESU托儿、休闲服务;- 技能发展系统:培训、职业咨询;- 社会支持:咨询与倾听、社会援助和贷款;- 假期和休闲服务:假期券、优惠住宿;- 体育和文化活动;- 集体餐饮。

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  1. CONNECT:[ UseTime:0.000469s ] mysql:host=127.0.0.1;port=3306;dbname=h_mffb;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `fenlei` [ RunTime:0.000720s ]
  3. SELECT * FROM `fenlei` WHERE `fid` = 0 [ RunTime:0.000291s ]
  4. SELECT * FROM `fenlei` WHERE `fid` = 63 [ RunTime:0.000279s ]
  5. SHOW FULL COLUMNS FROM `set` [ RunTime:0.000525s ]
  6. SELECT * FROM `set` [ RunTime:0.000226s ]
  7. SHOW FULL COLUMNS FROM `article` [ RunTime:0.000494s ]
  8. SELECT * FROM `article` WHERE `id` = 499709 LIMIT 1 [ RunTime:0.000575s ]
  9. UPDATE `article` SET `lasttime` = 1774769202 WHERE `id` = 499709 [ RunTime:0.002206s ]
  10. SELECT * FROM `fenlei` WHERE `id` = 64 LIMIT 1 [ RunTime:0.000256s ]
  11. SELECT * FROM `article` WHERE `id` < 499709 ORDER BY `id` DESC LIMIT 1 [ RunTime:0.000406s ]
  12. SELECT * FROM `article` WHERE `id` > 499709 ORDER BY `id` ASC LIMIT 1 [ RunTime:0.000434s ]
  13. SELECT * FROM `article` WHERE `id` < 499709 ORDER BY `id` DESC LIMIT 10 [ RunTime:0.000787s ]
  14. SELECT * FROM `article` WHERE `id` < 499709 ORDER BY `id` DESC LIMIT 10,10 [ RunTime:0.001464s ]
  15. SELECT * FROM `article` WHERE `id` < 499709 ORDER BY `id` DESC LIMIT 20,10 [ RunTime:0.001779s ]
0.079428s