Postdoc in wind farm modeling and control using physics-informed deep learning

The Department of Mechanical and Production Engineering, Aarhus University, invites applications for a two-year postdoc position offering applicants an exciting opportunity to join the “Flow Physics and Turbulence” group to pursue research on efficient deep learning techniques for wind farm modeling, optimization, and control.

The project is fully funded by the Independent Research Fund Denmark (IRFD/DFF Green Transition). The main objective of the project is to enable data-driven deep learning models for fast-paced engineering design and decision making in both academia and wind-energy industries. In pursuit of this objective, this project aims to develop physics-informed data-based models for wind farm flow simulations, optimization and control through deep learning.

The project has an interdisciplinary nature, and you will be a member of the “Flow Physics and Turbulence” group at the Department of Mechanical and Production Engineering (MPE) and the “Machine Learning and Computational Intelligence” group at the Department of Electrical and Computer Engineering (ECE). The former is specializing in modeling and simulating turbulent flows, in wind engineering and renewable energy, and in reduced-order modeling. The latter is specializing in both theoretical and applied aspects of machine learning and its sub-areas (like deep learning and statistical machine learning). In recent years, these research groups have seen close cooperation between different research groups around the world. For more information about the group’s work, see

Flow Physics and Turbulence (au.dk)
and
Machine Learning and Computational Intelligence (au.dk)

Starting Date and Period
The position is for 2021 and is available from May 1st or as soon as possible hereafter.

Job description
Research involves a synergistic combination of numerical modeling and theoretical development of physics-based and physics-informed machine learning models. You are expected to contribute to research and development in deep learning methodologies for wind farm flow modeling, optimization, and control. This includes proposal of new methodologies, implementation and validation of the methods using the simulation and observational data, reporting of the results, and dissemination in international conferences and journals.

Your profile
The successful candidate should hold a PhD degree with a background in Mechanical Engineering, Physics, or other related disciplines. It is expected that the candidates have expertise and research experience in the following areas: computational fluid dynamics; machine learning, wind energy; turbulence; atmospheric boundary layer flow; parallel computing. The candidate should also be able to collaborate in an interdisciplinary team. Excellent communication skills in English, in both speech and writing, are a requirement.

Who we are
The focus of our research in “Flow physics and Turbulence” group is to develop and test improved numerical models to predict the complex interaction between turbulent flows and the environment, with emphasis on wind energy systems. Our research involves a combination of numerical modeling, which is based on large-eddy simulation (LES) and Reynolds-averaged Navier-Stokes (RANS) techniques, and theoretical development. Our current research includes:

• Computational fluid dynamics (DNS/LES/RANS)
• Wind farm modeling, optimization and control
• Datadriven modeling
• Boundarylayer turbulence
• Uncertainty quantification

What we offer
As a Postdoctoral Researcher, you will be a valuable member of the group and the department at Aarhus University. You will be given the opportunity to co-supervise PhD students working in related topics. You will have the opportunity to disseminate results of the group through participating in Conferences, Workshops and meetings related to our work.

Place of Work
The place of employment is Aarhus University, and the place of work is the Department of Mechanical and Production Engineering, Navitas Building, Inge Lehmanns Gade 10, 8000 Aarhus C, Denmark.

Contact Information
Further information about the position may be obtained from / For further information please contact:
Associate Professor Mahdi Abkar
Email: abkar@eng.au.dk
Tel. number: +45 93 52 16 94

Associate Professor Alexandros Iosifidis
Email: ai@eng.au.dk
Tel. number: +45 93 50 88 75

Deadline
March 15th, 2021

Application procedure
Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment committee if necessary, – the head of department selects the candidates to be evaluated. All applicants will be notified whether or not their applications have been sent to an expert assessment committee for evaluation. The selected applicants will be informed about the composition of the committee, and each applicant is given the opportunity to comment on the part of the assessment that concerns him/her self. Once the recruitment process is completed a final letter of rejection is sent to the deselected applicants.

Letter of reference
If you want a referee to upload a letter of reference on your behalf, please state the referee’s contact information when you submit your application. We strongly recommend that you make an agreement with the person in question before you enter the referee’s contact information, and that you ensure that the referee has enough time to write the letter of reference before the application deadline.
Unfortunately, it is not possible to ensure that letters of reference received after the application deadline will be taken into consideration.

Formalities and salary range
Technical Sciences refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation.

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found here.

Appointment shall be in accordance with the collective labour agreement between the Danish Ministry of Finance and the Danish Confederation of Professional Associations. Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities.

Salary depends on seniority as agreed between the Danish Ministry of Finance and the Confederation of Professional Associations.

All interested candidates are encouraged to apply, regardless of their personal background. Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity.

Aarhus University offers a broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners. Read more here. Please find more information about entering and working in Denmark here.

Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here.

The application must be submitted via Aarhus University’s recruitment system, which can be accessed under the job advertisement on Aarhus University's website.

Aarhus University
Aarhus University is an academically diverse and research-intensive university with a strong commitment to high-quality research and education and the development of society nationally and globally. The university offers an inspiring research and teaching environment to its 38,000 students (FTEs) and 8,000 employees, and has an annual revenues of EUR 885 million. Learn more at www.international.au.dk/