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Position: PhD position on data-driven surrogate modelling for floating wind turbines
Institution: Delft University of Technology
Location: Delft, South Holland, Netherlands
Duties: The PhD candidate will develop and apply a surrogate model based on Gaussian process regression to predict the local aerodynamic characteristics of floating wind turbines. The candidate will generate an initial training dataset based on the results of a free wake vortex model coupled to the engineering tool OpenFAST. They will also be able to train the surrogate model on higher-fidelity data delivered by another PhD project
Requirements: An MSc. degree in wind energy, scientific computing, aerospace engineering, mechanical engineering, offshore engineering, or a related field; Fundamental knowledge in the field of numerical techniques and wind energy, knowledge in machine learning or floating wind energy is a plus; You enjoy working independently: Creativity, auto-didactic capabilities, and a strong research-oriented attitude; Fluency in English
   
Text: Activeer hoog contrast Ga naar hoofdcontent Home van TU Delft Werken bij TU Delft Vacatures Wetenschapper PhD Tenure track Postdoc Professional Zoeken Werken bij TU Delft Vacatures Menu sluiten Wetenschapper PhD Tenure track Postdoc Professional Dit is het social media blok facebook twitter instagram youtube linkedin whatsapp whatsapp English Sluit menu Zoeken Sluit zoek Werken bij TU Delft Vacatures Job details PhD position on data-driven surrogate modelling for floating wind turbines Apply Now Floating wind turbines aerodynamics is a rapidly growing research field. Wind turbines that are placed on a floating support structure experience unsteady aerodynamics, which can negatively affect rotor performance and fatigue loads. There is a need to develop fast models that can predict the unsteady aerodynamics of floating wind turbines under fully nonlinear metocean conditions and quantify the associated uncertainties. Job description The PhD candidate will develop and apply a surrogate model based on Gaussian process regression to predict the local aerodynamic characteristics of floating wind turbines. The candidate will generate an initial training dataset based on the results of a free wake vortex model coupled to the engineering tool OpenFAST. They will also be able to train the surrogate model on higher-fidelity data delivered by another PhD project. The PhD candidate will work as part of the project DataFlowt, “Physics-informed data-driven modelling and control of floating wind turbines”, funded by the Dutch national research council under the Talent Programme Vidi scheme. The candidate will work in a vibrant research group and will interface with ongoing large research projects in the field, e.g. STEP4WIND (step4wind.eu), as well as engage with the activities of the Floating Renewables Lab at TU Delft. We are specifically looking for a researcher with a relevant background and strong interest in numerical modelling, machine learning, wind energy, wind turbine design, and metocean conditions. Does this project excite you? Then you might be the right candidate for this position. A short description of your motivation and an up-to-date curriculum vitae is required to apply for this position. Requirements - An MSc. degree in wind energy, scientific computing, aerospace engineering, mechanical engineering, offshore engineering, or a related field; - Fundamental knowledge in the field of numerical techniques and wind energy, knowledge in machine learning or floating wind energy is a plus; - You enjoy working independently: Creativity, auto-didactic capabilities, and a strong research-oriented attitude; - Fluency in English; - The capacity to communicate effectively with peers, students and stakeholders in the application field; - An open personality and good communication skills in written and spoken English. You thrive in transferring knowledge and presenting your work to larger audiences; - Ability to present challenges and results clearly; - Potential in being a positive and open-minded supervisor for (graduate) students. Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements. Conditions of employment Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation. TU Delft (Delft University of Technology) Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. Challenge. Change. Impact! Faculty Aerospace Engineering The Faculty of Aerospace Engineering at Delft University of Technology is one of the world’s most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 250 PhD candidates and over 2,700 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond. Click here to go to the website of the Faculty of Aerospace Engineering. The Department of Flow Physics and Technology (FPT) is one of four departments composing Aerospace Engineering. Fundamental research is performed in the Aerodynamics section. Aircraft design, propulsion systems and their integration are the main topics in the FPP section. Wind energy systems, from small wind turbines to large offshore farms, are the objective of the research of the Wind Energy Section. The department operates comprehensive laboratories, equipped with modern wind tunnels and state-of-the-art measurement systems. The Wind Energy Section facilitates the development of wind energy technology and the expansion of the use of wind power through research and education. In its research activities there is a focus on large multi megawatt offshore wind turbines and offshore wind farms, though urban and airborne wind power is also addressed. Both technology development aspects as well as fundamental aspects are present in the research program. With respect to educational courses, the BSc and MSc level are offered for Aerospace students, SET students and for the European Wind Energy Master (EWEM) students. Additional information For more information about this position, please contact Dr. Axelle Viré, a.vire@tudelft.nl Application procedure Are you interested in this vacancy? Please apply before 08-10-2022 via the application button and upload your motivation and CV. A pre-employment screening can be part of the selection procedure. Applying for an exemption for specific research and educational areas is an obligatory part of the selection procedure for this vacancy. This exemption must be obtained from the Ministry of Education, Culture and Science (OCW) before an employment contract is agreed upon. Click here for more information. You can apply online. We will not process applications sent by email and/or post. Acquisition in response to this vacancy is not appreciated. Faculty/Department Faculty of Aerospace Engineering Job Type PhD Scientific field Natural sciences Hours per week 38-40 Salary € 2.541,00 - € 3.247,00 Desired level of education University graduate Vacancy number TUD02752 Method of applying Via system Floating wind turbines aerodynamics is a rapidly growing research field. Wind turbines that are placed on a floating support structure experience unsteady aerodynamics, which can negatively affect rotor performance and fatigue loads. There is a need to develop fast models that can predict the unsteady aerodynamics of floating wind turbines under fully nonlinear metocean conditions and quantify the associated uncertainties. Job description The PhD candidate will develop and apply a surrogate model based on Gaussian process regression to predict the local aerodynamic characteristics of floating wind turbines. The candidate will generate an initial training dataset based on the results of a free wake vortex model coupled to the engineering tool OpenFAST. They will also be able to train the surrogate model on higher-fidelity data delivered by another PhD project. The PhD candidate will work as part of the project DataFlowt, “Physics-informed data-driven modelling and control of floating wind turbines”, funded by the Dutch national research council under the Talent Programme Vidi scheme. The candidate will work in a vibrant research group and will interface with ongoing large research projects in the field, e.g. STEP4WIND (step4wind.eu), as well as engage with the activities of the Floating Renewables Lab at TU Delft. We are specifically looking for a researcher with a relevant background and strong interest in numerical modelling, machine learning, wind energy, wind turbine design, and metocean conditions. Does this project excite you? Then you might be the right candidate for this position. A short description of your motivation and an up-to-date curriculum vitae is required to apply for this position. Requirements - An MSc. degree in wind energy, scientific computing, aerospace engineering, mechanical engineering, offshore engineering, or a related field; - Fundamental knowledge in the field of numerical techniques and wind energy, knowledge in machine learning or floating wind energy is a plus; - You enjoy working independently: Creativity, auto-didactic capabilities, and a strong research-oriented attitude; - Fluency in English; - The capacity to communicate effectively with peers, students and stakeholders in the application field; - An open personality and good communication skills in written and spoken English. You thrive in transferring knowledge and presenting your work to larger audiences; - Ability to present challenges and results clearly; - Potential in being a positive and open-minded supervisor for (graduate) students. Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements. Conditions of employment Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation. TU Delft (Delft University of Technology) Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. Challenge. Change. Impact! Faculty Aerospace Engineering The Faculty of Aerospace Engineering at Delft University of Technology is one of the world’s most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 250 PhD candidates and over 2,700 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond. Click here to go to the website of the Faculty of Aerospace Engineering. The Department of Flow Physics and Technology (FPT) is one of four departments composing Aerospace Engineering. Fundamental research is performed in the Aerodynamics section. Aircraft design, propulsion systems and their integration are the main topics in the FPP section. Wind energy systems, from small wind turbines to large offshore farms, are the objective of the research of the Wind Energy Section. The department operates comprehensive laboratories, equipped with modern wind tunnels and state-of-the-art measurement systems. The Wind Energy Section facilitates the development of wind energy technology and the expansion of the use of wind power through research and education. In its research activities there is a focus on large multi megawatt offshore wind turbines and offshore wind farms, though urban and airborne wind power is also addressed. Both technology development aspects as well as fundamental aspects are present in the research program. With respect to educational courses, the BSc and MSc level are offered for Aerospace students, SET students and for the European Wind Energy Master (EWEM) students. Additional information For more information about this position, please contact Dr. Axelle Viré, a.vire@tudelft.nl Application procedure Are you interested in this vacancy? Please apply before 08-10-2022 via the application button and upload your motivation and CV. A pre-employment screening can be part of the selection procedure. Applying for an exemption for specific research and educational areas is an obligatory part of the selection procedure for this vacancy. This exemption must be obtained from the Ministry of Education, Culture and Science (OCW) before an employment contract is agreed upon. Click here for more information. You can apply online. We will not process applications sent by email and/or post. Acquisition in response to this vacancy is not appreciated. Back to list Send job to a friend Print this page Apply Now Five reasons to work at the TU Delft 1. Impact: for a better society at a top international university 2. Open international community with multidisciplinairy teamwork 3. Excellent facilities for research, education and innovation 4. Room for personal growth 5. Good employment conditions Read more! Read more! Technische Universiteit Delft Dit is het social media blok Postbus 5 2600 AA Delft Tel: 31 (0)15 27 89111 Activeer hoog contrast Zoeken /* */ AddThis Sharing Sidebar Hide Show Close
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