PhD scholarship in Uncertainty Quantification & Technology Qualification fo 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

Uncertainty Quantification, Digital Twinning, Machine Learning, Probabilistic Modelling, Statistical Modelling, Bayesian Inference, Stochastic Modelling, Computational Modelling, Data Analytics, Structural Mechanics, Material Modelling, Multi-Physics Simulation, Reliability Assessment, Wind Energy Systems, Certification Frameworks, Scientific Programming

Industry

Description

If you are aspiring to shape the future of industrial R&D or academia - particularly in the rapidly evolving areas of uncertainty quantification, digital twinning, and advanced material technologies - this PhD position offers a unique opportunity. As part of MET2ADAPT, you will investigate some of the most challenging and high-impact questions surrounding the validation, certification, and long-term performance of next-generation wind turbine components enhanced with meta-materials. We are seeking a motivated, analytical, and ambitious researcher who is passionate about enabling safer, more reliable, and more sustainable renewable energy systems. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods, machine learning tools, and simulation techniques. If you thrive at the intersection of engineering, data, and advanced computational science, this position will allow you to contribute meaningfully to the green transition while shaping the future of turbine technology. 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 Uncertainty Quantification and Technology Qualification for Advanced 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 focus on developing a robust framework for uncertainty quantification (UQ) and technology qualification, aimed at validating the safety, performance, and longevity of advanced wind turbine components, particularly next-generation blades featuring adaptive meta-materials. The UQ model will address the intrinsic uncertainties arising from the mechanical and aerodynamic properties of turbine blades, including variances in material behaviour under extreme load conditions, manufacturing tolerances, and stochastic environmental factors such as fluctuating wind speeds and saltwater exposure. Using advanced statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will quantify and analyse uncertainties in the design and operational performance of these components. This process will support the creation of a technology qualification framework that establishes rigorous performance benchmarks, aiding in compliance with certification standards (e.g., IEC, DNV) and streamlining the pathway to commercialization. Key objectives include ensuring that the qualification framework is adaptable to evolving standards and technological advances, promoting faster adoption of innovative turbine designs. Close collaboration with industry partners will allow the UQ and technology qualification models to be tested and validated against real-world data, ensuring practical applicability. Ultimately, the project aims to enhance the robustness and reliability of wind turbines, enabling resilient renewable energy solutions that are safe, effective, and efficient over their intended lifecycle. 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 focus on developing an advanced framework for uncertainty quantification (UQ) and technology qualification for next-generation wind turbine components, including blades enhanced with adaptive meta-materials. You will work on modelling the sources and propagation of uncertainties arising from material behaviour, aerodynamic and structural loading, environmental exposure, and manufacturing variability, and determine how these factors influence performance, safety, and lifetime predictions. Your research will involve constructing probabilistic and statistical models—such as Bayesian inference, stochastic simulation, and surrogate modelling—to quantify performance envelopes, reliability metrics, and certification-relevant indicators. A central aspect of your work will be integrating these UQ methods into digital-twin platforms, enabling continuous reliability assessment and supporting compliance with international qualification and certification standards. This project will be carried out in close collaboration with academic and industrial partners across the MET2ADAPT consortium. The PhD provisionally includes 3 months secondments (indicatively) at: Columbia University (USA) for advanced training in stochastic modelling and rare-event analysis. University of Trento (Italy) to link UQ models with meta-material configurations and nonlinear dynamics. University of Granada (Spain) for coupling reliability analysis with technology-qualification frameworks. 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, physics, data science or a related discipline, along with solid skills in computational modelling, statistics, or machine learning. An interest in probabilistic modelling, structural reliability, or certification processes is highly desirable. Your ability to reason rigorously, work independently yet collaboratively, and bridge computational methods with practical engineering considerations will be essential in advancing safer and more reliable renewable energy technologies. To be considered for this position, you must have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. For this PhD project, we expect candidates to have demonstrated experience or a strong interest in topics related to uncertainty quantification, probabilistic modelling, and the validation of advanced wind turbine components. Experience in one or more of the following areas will be considered highly advantageous: Scientific programming in Python or MATLAB Probabilistic methods, Bayesian inference, or stochastic modelling Structural mechanics, material modelling, or multi-physics simulation Data analytics, digital-twin technologies, or reliability assessment Wind energy systems, certification frameworks, or related engineering domains 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 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 February 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 a framework for uncertainty quantification and technology qualification for advanced wind turbine components. Your research will involve modelling uncertainties and integrating methods into digital-twin platforms for continuous reliability assessment.