PhD scholarship in Risk-Based Maintenance Planning for Wind Turbine Compone at Danmarks Tekniske Universitet

Roskilde, Region Zealand, Denmark -

Full Time

Start Date

Immediate

Expiry Date

16 Apr, 26

Salary

0.0

Posted On

16 Jan, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Engineering, Applied Mathematics, Data Science, Programming, Quantitative Modelling, Risk Analysis, Structural Reliability, Digital Twin Technologies, Data Analytics, SHM, SCADA, Maintenance Planning, Scientific Programming, Probabilistic Modelling, Wind Energy Systems

Industry

Description

If you are aspiring to shape the future of industrial R&D or academia, especially in the rapidly advancing fields of meta-materials, renewable energy systems, and intelligent structural technologies, this PhD position offers a unique opportunity. Join MET2ADAPT to engage with some of the most challenging and high-impact questions surrounding next-generation wind and wave energy systems, digital twins, and resilient structural design. We are looking for a motivated, curious, and ambitious researcher committed to accelerating the green transition by advancing adaptive materials, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts at the intersection of engineering, data, and emerging technologies. DTU Wind and Energy Systems, in collaboration with leading industrial and academic partners in renewable energy, including NADARA, a major European operator of onshore wind assets, invites applications for a fully funded PhD position on Risk-Based Maintenance Planning for Wind Turbine Components. This position is part of the MET2ADAPT Doctoral Network (Meta-Materials and Meta-Structures for Adaptable, Resilient and Sustainable Renewable Energy Power Plants), a prestigious Marie Skłodowska-Curie Doctoral Network funded by the European Union. As a Doctoral Candidate in MET2ADAPT, you will create a comprehensive risk assessment and maintenance planning framework for wind turbine technologies, with a focus on enhancing structural resilience and operational efficiency. Key objectives include the development of a tailored risk-based inspection (RBI) and risk-centered maintenance (RCM) model to address specific vulnerabilities in wind turbine components, such as blade erosion, fatigue cracking, and high-cycle fatigue. The model will focus on critical structural issues, including leading-edge erosion, hydrogen embrittlement in marine environments, and load-induced wear on turbine blades and support structures. Additionally, a digital tool will be developed to allow operators to visualize real-time risk indicators, maintenance sched-ules, and preventive repair alerts, facilitating optimized maintenance decisions and reducing unplanned downtimes. The framework will be validated through close collaboration with industry partners, incorporating actual operational data and ensuring that the model meets practical industry needs. You will be part of a cohort of 16 international PhD researchers benefiting from interdisciplinary training across Europe, including thematic training weeks, specialist workshops, and transferable-skills courses central to the MSCA programme. Your research will be based at DTU’s Risø campus, a leading international hub for wind energy research, providing an inspiring, collaborative, and industry-connected working environment. Close collaboration with NADARA will allow you to apply and validate your methods using real operational data from a large wind turbine portfolio. Project Responsibilities and Qualifications As a Doctoral Candidate in the MET2ADAPT network, your primary research tasks will centre on the development of advanced methodologies for risk-based inspection and maintenance planning in wind turbine systems. You will work on designing a robust, data-driven decision framework that integrates structural models, probabilistic degradation processes, and operational monitoring data. Your research will focus on identifying how emerging meta-material technologies and evolving environmental conditions influence deterioration and maintenance needs. You will analyse SHM, SCADA, and environmental datasets to extract meaningful indicators of asset health, assess key degradation modes, and quantify their influence on remaining useful life. A major component of your work will involve building and validating digital-twin-assisted tools that support real-time maintenance decisions, optimised inspection scheduling, and improved operational reliability. This research will be conducted in close collaboration with both academic and industrial partners across the MET2ADAPT consortium. The project includes 3 month secondments at: • NADARA (Portugal/UK), providing extensive industry exposure, access to real-world operational data, and insights into large-scale O&M practices. • ETH Zürich (Switzerland), supporting academic collaboration in SHM data processing, sensor-driven prognosis, and complementary supervision. These secondments form an integral part of your training and will contribute significantly to the interdisciplinary and intersectoral nature of your PhD. Applicants should have a strong academic background in engineering, applied mathematics, data science or a related discipline, together with solid skills in programming and quantitative modelling. An interest in risk analysis, structural reliability or digital twin technologies is highly desirable. Your ability to think rigorously, work systematically, and integrate modelling with practical engineering decision-making will be key to advancing more sustainable and efficient maintenance solutions for the renewable energy sector. To be considered for this position, you must have a two-year master’s degree (120 ECTS points) or an equivalent academic qualification at the same level. For this PhD project, we expect candidates to have demonstrated experience or a strong interest in areas relevant to risk-based maintenance, structural modelling, and data-driven decision support for wind energy systems. In particular, experience in one or more of the following areas will be considered highly beneficial: Scientific programming in Python or MATLAB Structural mechanics, reliability analysis, or probabilistic modelling Data analytics, SHM/SCADA data interpretation, or digital-twin technologies Wind energy systems, maintenance planning, or related engineering topics You should be able to work effectively within a collaborative, interdisciplinary research environment while also taking responsibility for your individual research objectives and deliverables. As this position is funded under the Marie Skłodowska-Curie Doctoral Network (MSCA DN) programme, applicants must also meet the following eligibility criteria: Not already hold a doctoral degree (i.e., you must not have been awarded a PhD at the time of recruitment). Comply with the MSCA mobility rule: you must not have resided or carried out your main activity (work, studies, etc.) in Denmark for more than 12 months in the 3 years immediately prior to the recruitment date. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education. We offer We offer you the opportunity to become part of MET2ADAPT, a doctoral network designed to equip sixteen Doctoral Candidates with deep technical expertise, strong interdisciplinary competence, and a broad set of transferable skills. As a member of this network, you will engage with leading academic institutions and industrial partners across Europe, gaining exposure to both cutting-edge research environments and real-world operational challenges in renewable energy. Through secondments, training schools, and collaborative research activities, you will develop a comprehensive understanding of the full pathway from scientific discovery to technological innovation and industrial implementation, while building a strong professional network that will support your future career. MET2ADAPT trains a new generation of creative, entrepreneurial, and resilient researchers who are prepared to address emerging challenges in the renewable energy sector. The programme focuses on advancing intelligent meta-materials, digital twinning, autonomous monitoring, and risk-informed decision methodologies that will contribute to safer, more efficient, and more sustainable energy systems. Upon completing the programme, you will be equipped to translate research-driven insights into impactful technologies, tools, and services that generate both economic and societal value. DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. Salary and appointment terms The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. You can read more about career paths at DTU here. Further information Further information may be obtained from Professor Athanasios Kolios, atko@dtu.dk You can read more about DTU Wind at https://wind.dtu.dk/ If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. Application procedure Your complete online application must be submitted no later than 10 March 2026 (23:59 Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include: A letter motivating the application (cover letter) Curriculum vitae Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale You may apply prior to obtaining your master's degree but cannot begin before having received it. Applications received after the deadline will not be considered. All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply. DTU Wind is about taking the technology to the next level. About creating an impact for people and society through research and innovation. About collaborating with the entire energy sector to develop the most effective technology on the planet. Our research spans the full spectrum of wind and energy systems. From investigating nanoscale structures to macro-scale atmospheric flow; from designing the turbines of tomorrow to the digital energy solutions of the future; from developing electric power systems to exploring more democratic processes for project planning. Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

Responsibilities

As a Doctoral Candidate, you will develop advanced methodologies for risk-based inspection and maintenance planning in wind turbine systems. Your work will involve creating a data-driven decision framework that integrates structural models and operational monitoring data.