RE-ADVERTISEMENT: Postdoc position in Data-driven Model Discovery for Turbulent Flows at the Department of Electrical and Computer Engineering, AU

The Department of Electrical & Computer Engineering, Aarhus University invites applications for a 2-year postdoc position offering applicants an exciting opportunity to join the Machine Learning & Computational Intelligence research group to pursue research on efficient machine learning (ML) techniques for simulations, reduced-order modeling and optimization of wall-bounded turbulent flows. The contract will be for two years.

The project is fully funded by the Villum Foundation (Villum Synergy Programme) and is a synergy between the Machine Learning & Computational Intelligence group at the Department of Electrical and Computer Engineering and the Fluid Mechanic and Turbulence group at the Department of Mechanical & Production Engineering . The main objective of this project is to enable data-driven fluid mechanics for fast-paced engineering design and decision-making. In pursuit of this objective, this project aims to develop physics-integrated data-driven models for simulations of wall-bounded turbulent flows through ML.

You will be a member of the Machine Learning & Computational Intelligence group at the Department of Electrical and Computer Engineering and closely collaborate with members of the Flow Physics and Turbulence group at the Department of Mechanical and Production Engineering. The research groups are specialized in machine/deep learning, statistical machine learning, data-driven analytics, modeling and simulation of turbulent flows, data-driven techniques, and reduced-order modeling. For more information about the groups’ work, see:
Machine Learning and Computational Intelligence (au.dk)
Fluid Mechanics and Turbulence (au.dk)

Expected start date and duration of employment

This is a 2-year position and is available from 01.07.2024 or as soon as possible hereafter.

Job description

Research in this project involves a synergistic combination of numerical modeling and theoretical development of physics-integrated ML models in numerical simulations of turbulent flows. You are expected to contribute to research and development in machine learning methodologies for simulations, reduced-order modeling, and optimization of wall-bounded turbulent flows. 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 Computer Engineering/Science, Mechanical Engineering, Physics, or related disciplines.

It is expected that the candidates have expertise and research experience in the following areas:   

• Machine learning, Computational fluid mechanics, 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 Machine Learning and Computational Intelligence group, led by

Professor Alexandros Iosifidis

, focuses on machine learning techniques and methods targeting a variety of applications involving many types of data, like images, time-series, sensor data, generic graph structures, attribute data and multi-faceted data. Our current contributions are in the fields of Computer Vision, Computational Finance, Bioscience, Robotics and Social/Financial Networks.

The focus of the Fluid Mechanics 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.  Our mission is to support our industrial partners toward the full green transition and digitalization of society in the area of thermo-fluids engineering.

What we offer

As a postdoctoral researcher, you will be a valuable member of the group and the ECE 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.

Read more about ECE at our

webpage

or our

LinkedIn

.

Place of work and area of employment

The place of work is Finlandsgade 22, 8200 Aarhus N, Denmark.

Contact information

For further information please contact:

Deadline

Applications must be received no later than 15.04.2024.

Previously submitted applications will be taken into consideration unless they are withdrawn.

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 Taxation 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 Taxation 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.