项目介绍

2026年8月20日

Do you want to investigate the resilience of critical raw material supply chains supporting low-carbon and digital technologies? Join us as a PhD student at SDU Life Cycle Engineering, University of Southern Denmark.

The Department of Green Technology at the University of Southern Denmark invites applications for a three-year PhD position in data-driven critical raw material supply chain resilience.

The position will be based at SDU Life Cycle Engineering, Department of Green Technology, Faculty of Engineering, at the SDU Odense campus. The expected starting date is 15 February 2027, or as soon as possible thereafter.

Project Overview

The deployment of low-carbon technologies, electrification and digital infrastructure is increasing global demand for critical raw materials. At the same time, the production and processing of many of these materials are geographically concentrated and exposed to geopolitical, economic, environmental and logistical disruptions.

Understanding how technology development affects material demand, in-use stocks, end-of-life flows and global supply dependencies is therefore important for assessing and strengthening the resilience of critical raw material supply chains.

The PhD position is jointly funded through research projects on critical raw material supply chains and material requirements for Denmark’s climate-neutral transition. The project will be embedded in an interdisciplinary research environment combining environmental systems analysis, supply-chain research and data science.

PhD Topic Description

The PhD project will develop modular and data-driven approaches for analysing critical raw material demand, supply-chain dependencies and resilience.

A central methodological contribution will be the development of transparent, reusable and reproducible computational modules for dynamic material flow analysis. The modules will support the integration of technology deployment scenarios, material intensities, product lifetimes, stocks and flows, end-of-life management, recycling, production, trade, facility and ownership data.

The developed approaches will be applied to selected technology systems, including Denmark’s wind-energy infrastructure and the rapidly expanding infrastructure supporting data centres and AI computing. These cases will be analysed within a common methodological framework to examine how infrastructure expansion and technological change influence demand for critical and scarce materials, in-use stocks, future waste flows, recycling potential and global supply-chain dependencies.

The project may also investigate overlapping material requirements and competition for materials across low-carbon and digital technologies. Particular attention may be given to supply concentration, host–by-product dependencies, trade and ownership structures, supply bottlenecks, cascading risks and potential resilience strategies.

Depending on the candidate’s academic background and the specific research questions, the project may include network analysis, geospatial analysis, scenario modelling, uncertainty analysis, machine learning and other AI-supported approaches.

The candidate will build on selected existing models, datasets and research activities in the group and further develop scientifically robust and reusable methods that improve transparency, comparability and reproducibility in material-system research.

The exact research focus and detailed PhD plan will be developed jointly with the successful candidate, taking into account the project objectives, academic background and research interests.

In addition to a PhD dissertation and high-quality scientific publications, the project is expected to produce reusable modelling methods, documented datasets and reproducible computational workflows.

PhD Position and Research Environment

As a PhD student, you will conduct independent research under the supervision of an interdisciplinary team, contribute to high-quality scientific publications and participate actively in a collaborative research environment.

You will join SDU Life Cycle Engineering, where research covers industrial ecology, material flow analysis, life cycle assessment, circular economy, resource systems and sustainability transitions.

The project connects expertise in engineering, data science, mathematics, business, supply-chain research and geological resources. The wider research environment includes competences in material flow analysis, critical raw material systems, data mining, network analysis, supply-chain science, finance, investment, ownership structures, geological resources and technology systems.

The position provides opportunities for collaboration across SDU faculties and with external research partners. It may also include participation in international conferences, research visits and collaboration with relevant industrial and public-sector stakeholders.

The PhD programme follows the Danish PhD framework and includes coursework, participation in active research environments, dissemination activities, and teaching or other knowledge-dissemination duties.

What We Expect

We are looking for a highly motivated, independent and collaborative candidate with a strong interest in critical raw materials, quantitative modelling, data-driven research and sustainability.

Applicants must hold a relevant master’s degree or equivalent by the time of enrolment. Relevant academic backgrounds may include engineering, industrial ecology, sustainability science, resource management, data science, computer science, applied mathematics, operations research, supply-chain management, geoinformatics, mining or geological sciences, or another relevant natural science or quantitative discipline.

The successful candidate should demonstrate:

• A solid academic foundation in quantitative analysis, system modelling, data science or related methods. 
• Experience with programming and data analysis, preferably using Python or a similar programming language. 
• Experience with data handling, including data cleaning, transformation, integration and exploratory analysis. 
• Strong analytical and problem-solving skills. 
• The ability to work independently and collaboratively in an interdisciplinary research environment. 
• Good written and spoken English. 
• A strong interest in sustainability, critical raw materials and supply-chain resilience. 

Experience in one or more of the following areas will be considered an advantage:

• Material flow analysis, industrial ecology or material systems modelling. 
• Network, supply-chain or geospatial analysis. 
• Scientific computing and reproducible research workflows. 
• Statistics, machine learning, artificial intelligence, optimisation, uncertainty or scenario analysis. 
• International trade, production facility or corporate ownership data. 
• Critical raw materials, wind energy, digital infrastructure or data centres. 

Applicants are not expected to possess expertise in all these areas. Prior experience with material flow analysis is an advantage but is not a requirement. Relevant training will be provided according to the candidate’s background and the needs of the project.

Application

Before applying the candidates are advised to read the Faculty information for prospective PhD students and the SDU information on how to apply.

The application must be submitted in English through the SDU online recruitment system.

Assessment of applicants will be based on the submitted application material. The application must include:

• Curriculum Vitae. 
• A motivated application describing the applicant’s research interests, relevant qualifications and motivation for applying. 
• Documentation of academic qualifications, including bachelor’s and master’s degree certificates and complete transcripts of grades. 
• Official English translations of documents not issued in English or Danish. 
• Two letters of recommendation. 
• A list of publications and up to two examples of relevant publications, if available. 
• The completed TEK PhD application form for 5+3 applicants. Find the form at the Faculty website.
• The completed TEK form for calculation of grade-point average. Find the form at the Faculty website.
• Official documentation describing the grading system of the awarding university, if the degree was not obtained in Denmark. 
• Examples of relevant thesis work, software, code repositories or other research outputs, where available. 
• Only for applicants from programmes that evaluate thesis/examination project by approved/not approved: An official written assessment of the thesis or dissertation project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme.