About the position
The Faculty of Science and Technology at the Norwegian University of Life Sciences (NMBU) has a vacant PhD–position related to computational fluid dynamics, machine learning and offshore wind energy. The PhD position is for a period of 3 years, or up to 4 years if teaching and other work duties are agreed.
Global wind power is expected to grow three times over the next decade to avoid the worst impact of climate change. The wind power plants are constructed with turbines having large rotor diameters to allow maximum energy yield from the oncoming wind. Special attention is given to reducing the cost of energy and increasing profitability, and this is anticipated to be achieved by developing optimized design, analysis, prediction, and monitoring tools capable of simulating aerodynamic flows accurately in offshore wind farms. To this end, traditional analytical tools employed to model aerodynamic flows in a wind farm are fast but include simplifications that can compromise the overall integrity of solutions. On the other hand, high-fidelity flow models based on computational fluid dynamics (CFD) are more accurate but at the same time require significantly high computational resources to obtain meaningful results.
The Ph.D. project aims to conduct research and innovation in flow simulation in offshore wind turbines by combining high-fidelity computational fluid dynamics (CFD) models with machine learning (ML) models. The developed state-of-the-art models are expected to be integrated into future digital twin technology to fulfill the industrial needs of computationally efficient tools and form a basis for condition monitoring, prediction, analysis, and maintenance of offshore wind turbines. Key research areas that will be exploited in the Ph.D. research project will be physics-based and data-driven Reduced Order Models (ROM) to simulate and predict wind farm flows, especially in the wake region.
An application for a PhD position at NMBU is at the same time an application for admission to a PhD programme at the institution. The documentation that is necessary to ensure that the admission requirements are met must be uploaded as an attachment.
Main tasks
The objective of the Ph.D. is to
- Carry out research on high fidelity simulation, physics-based and data-driven models for modeling and simulation of offshore wind turbines.
- Take part in the mandatory PhD research education program.
- Conduct independent research and publish in recognized scientific journals and conference proceedings.
The above may require conducting high fidelity simulations using computational fluid dynamics (RANS, LES) in OpenFOAM etc. on supercomputing infrastructures, development of methods based on Reduced Order Model (ROM) techniques with integration to machine learning and artificial intelligence methods (feed-forward networks, Artificial Neural Networks (ANN), etc.)
The position reports to Associate Professor M. Salman Siddiqui and the department head. Close collaboration is expected with Associate Professor Fadi Al Machot of data science department at NMBU, and other relevant research groups in Europe and China.
The successful candidate is expected to enter a plan for the progress of the work towards a PhD degree during the first months of the appointment, with a view to completing a doctorate within the PhD scholarship period.
Competence
The successful applicant must meet the conditions defined for admission to a PhD programme at NMBU. The applicant must have an academically relevant education corresponding to a five-year master’s degree or a cand.med.vet. degree, with a learning outcome corresponding to the descriptions in the Norwegian Qualification Framework, second cycle. Candidates submitting MSs thesis within 30. June 2022 may be considered. The applicant must have a documented strong academic background from previous studies and be able to document proficiency in both written and oral English. For more detailed information on the admission criteria please see the and the relevant .
The applicant must document expertise and interest in the research subject.
Required Academic qualifications
- MSc in Engineering, Applied/Numerical Mathematics, Atmospheric Sciences, Computer Science, Data Science. Physics or similar.
- Skills in numerical modeling and computational fluid dynamics (CFD).
- Experience in C, C++, Python or similar.
- Experience in use of opensource CFD softwares (OpenFOAM etc.).
The following experiences and skills will be emphasized:
- Self-driven with a strong ability to work independently when required.
- Experience in machine learning and deep learning.
- Coding Skills in Python using well-known libraries, e.g., TensorFlow, Sklearn or similar.
- Conduct independent research and publish the result in recognized scientific journals.
Remuneration and further information
The position is placed in government pay scale position code 1017.
PhD fellows are normally placed in pay grade 54 (NOK 491.200,-) on the Norwegian Government salary scale upon employment and follow ordinary meriting regulations.
Employment is conducted according to national guidelines for University and Technical College PhD scholars.
You can send specific questions about the PhD position or the research project to M. Salman Siddiqui, Associate Professor, Department of Mechanical Engineering and Technology Management, by email (do not use this e-mail for application, it is only for questions) Phone Logg inn for å se kontaktinformasjon
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Application
To apply online for this vacancy, please click on the 'Apply for this job' button above. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Application deadline: 31.05.2022
In the application, the candidate must confirm that information and documentation (in the form of attachments) submitted via the job application can also be used by NMBU in a possible admission process.
Applicants invited for an interview are expected to present original diplomas and certificates.
The following documents must be attached to the application:
- A cover letter where the applicant describes the personal motivation, summarising scientific work, and how the applicant sees her/his background suitable (maximum 1 page)
- Complete CV
- Certified copies of academic diplomas and certificates. (i.e. Di-ploma, transcript. Diploma supplement for both bachelor and master). Diplomas, transcripts and diploma supplements that are not in Norwegian or English must be uploaded in the original language. An English translation of these documents must also be attached.
- Applicants from universities outside Norway are kindly requested to send a diploma supplement, or a similar document, which describes in detail the study program and grading system.
- Documentation of proficiency in written and oral English in accordance with .
- Names and contact details for two references
- Additional relevant documentation of professional knowledge (for example, list of scientific works). If it is difficult to judge the applicant’s contribution for publications with multiple authors, a short description of the applicant’s contribution must be included.
About The Faculty of Science and Technology
develops research-based knowledge and educates civil engineers and lecturers needed to reach the UN's sustainability goals. We have approximately 150 employees, 70 PhD students and soon 1500 students. The education and research at REALTEK cover a broad spectrum of disciplines.
This includes data science, mechanics and process engineering, robotics, construction and architecture, industrial economics, environmental physics and renewable energy, geomatics, water and environmental engineering, applied mathematics as well as secondary school teacher education in natural sciences and use of natural resources such as in agriculture, forestry and aquaculture. The workplace is in Ås, 30 km from Oslo.
