The Department of Mechanical and Production Engineering, Aarhus University, invites applications for a 2-year postdoc position offering applicants an exciting opportunity to join the “Flow Physics and Turbulence” research group to pursue research on efficient machine learning techniques for turbulence modeling (i.e., wall and SGS modeling in LES), as well as reduced-order modeling of wall-bounded turbulence. The initial contract will be for two years.
The project is fully funded by the Independent Research Fund Denmark (DFF: Sapere Aude Research Leader Grant). The main objective of this project is to enable high-fidelity CFD tools for fast-paced engineering design and decision-making. In pursuit of this objective, this project aims to develop physics-constrained data-based turbulence models for scale-resolving simulations of wall-bounded turbulent flows through machine learning (ML). Data from direct numerical simulation (DNS) will be used for the development and validation of fine-scale models (i.e., wall and SGS models) in large-eddy simulation (LES). From an application standpoint, we will use the developed models for real-world flows such as scale-resolving simulations of turbulent flows in complex terrain and built environments. Throughout this project, we will closely collaborate with researchers at Penn State, Stanford University (CTR), and DTU.
You will be a member of the “Flow Physics and Turbulence” group at the Department of Mechanical and Production Engineering (MPE). The research group is specialized in modeling and simulation of turbulent flows, wind engineering and renewable energy, data-driven techniques, and reduced-order modeling of turbulence. For more information about the group’s work, see: Flow Physics and Turbulence (au.dk)
Research in this project involves a synergistic combination of numerical modeling and theoretical development of physics-based and physics-constrained ML models in scale-resolving simulations of turbulent flows. You are expected to contribute to research and development in machine learning methodologies for fine-scale modeling (i.e., both wall and SGS models) in LES as well as data-driven reduced-order modeling of wall-bounded turbulence. This includes proposal of new methodologies, implementation and validation of the methods using the simulation and experimental data, reporting of the results, and dissemination in international conferences and journals.
The focus of the “Flow physics and Turbulence” group led by Associate Professor Mahdi Abkar is to develop and test improved numerical models to predict the complex interaction between turbulent flows and the environment, with emphasis on energy systems.
The research involves a combination of numerical modeling and theoretical development. The current research includes:
- Computational fluid dynamics (DNS/LES/RANS)
- Thermo-fluid engineering
- Wind-farm modeling, optimization, and control
- Data-driven and machine-learning modeling of turbulence
- Uncertainty quantification & shape optimization
- An interdisciplinary environment with many national, international, and industrial collaborators.
- The opportunity to co-supervise PhD and MSc students working in related topics.
- A workplace characterised by professionalism, equality and a healthy work-life balance.
- Good salary based on the candidate experience.
Associate Professor Mahdi Abkar
Email: abkar@mpe.au.dk
Tel. number: +45 93 52 16 94
Applications must be received no later than 15 February 2022.
The project is fully funded by the Independent Research Fund Denmark (DFF: Sapere Aude Research Leader Grant). The main objective of this project is to enable high-fidelity CFD tools for fast-paced engineering design and decision-making. In pursuit of this objective, this project aims to develop physics-constrained data-based turbulence models for scale-resolving simulations of wall-bounded turbulent flows through machine learning (ML). Data from direct numerical simulation (DNS) will be used for the development and validation of fine-scale models (i.e., wall and SGS models) in large-eddy simulation (LES). From an application standpoint, we will use the developed models for real-world flows such as scale-resolving simulations of turbulent flows in complex terrain and built environments. Throughout this project, we will closely collaborate with researchers at Penn State, Stanford University (CTR), and DTU.
You will be a member of the “Flow Physics and Turbulence” group at the Department of Mechanical and Production Engineering (MPE). The research group is specialized in modeling and simulation of turbulent flows, wind engineering and renewable energy, data-driven techniques, and reduced-order modeling of turbulence. For more information about the group’s work, see: Flow Physics and Turbulence (au.dk)
Expected start date and duration of employment
This is a 2-year position and is available from 1 May 2022 or as soon as possible hereafter.
Job description
Research in this project involves a synergistic combination of numerical modeling and theoretical development of physics-based and physics-constrained ML models in scale-resolving simulations of turbulent flows. You are expected to contribute to research and development in machine learning methodologies for fine-scale modeling (i.e., both wall and SGS models) in LES as well as data-driven reduced-order modeling of wall-bounded turbulence. This includes proposal of new methodologies, implementation and validation of the methods using the simulation and experimental 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 either Mechanical Engineering, Atmospheric Sciences, Physics, or related disciplines. It is expected that the candidates have expertise and research experience in the following areas: computational fluid dynamics; machine learning, turbulence modeling; data-driven techniques, reduced-order modeling, dynamical system analysis, and 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 the “Flow physics and Turbulence” group led by Associate Professor Mahdi Abkar is to develop and test improved numerical models to predict the complex interaction between turbulent flows and the environment, with emphasis on energy systems.
The research involves a combination of numerical modeling and theoretical development. The current research includes:- Computational fluid dynamics (DNS/LES/RANS)
- Thermo-fluid engineering
- Wind-farm modeling, optimization, and control
- Data-driven and machine-learning modeling of turbulence
- Uncertainty quantification & shape optimization
What we offer
As a postdoctoral researcher, you will be a valuable member of the group and the MPE department at Aarhus University. The department offers:- An interdisciplinary environment with many national, international, and industrial collaborators.
- The opportunity to co-supervise PhD and MSc students working in related topics.
- A workplace characterised by professionalism, equality and a healthy work-life balance.
- Good salary based on the candidate experience.
Place of work and area of employment
The place of work is Inge Lehmanns gade 10, 8000 Aarhus C, and the area of employment is Aarhus University with related departments.Contact information
For further information please contact:Associate Professor Mahdi Abkar
Email: abkar@mpe.au.dk
Tel. number: +45 93 52 16 94
Deadline
Applications must be received no later than 15 February 2022.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.
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.
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.
Deadline15 Feb
Expected start1 May
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