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Reliability Modelling and Optimization group


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PhD degree co-supervised by Aarhus University and Grundfos

PhD degree co-supervised by Aarhus University and Grundfos

Do you want to contribute to industrial green transition and advance cutting-edge manufacturing technologies?

Do you want to pursue a PhD degree in collaboration between Aarhus University, Department of Mechanical and Production Engineering, and the Grundfos Advanced Manufacturing Engineering (AME) group.

Expected start date and duration of employment

This is a 3 year position with possible start from 1st of January 2024 or as soon a possible thereafter.

Project description:

The project will pioneer state-of-the-art manufacturing technologies for economically competitive and sustainable production of low-criticality rare earth permanent magnets with tunable material properties. The research will include:

  • Microstructure analysis, magnetic and mechanical performance assessment of rare earth permanent magnet materials
  • Experimental process development for advanced magnet production technologies, including sintering and upsetting
  • Finite element simulations of the above manufacturing processes and developing data- driven process optimization models
  • Validation and performance testing of magnetic materials
  • Disseminating the outcomes of the research work in top-tier academic venues, including peer-reviewed journal publications and scientific conference presentations

Qualifications and specific competences:

Master’s degree (120 ECTS or equivalent) in Mechanical Engineering, Manufacturing Engineering, Material Science & Engineering, or in a related discipline. 

Project team 

The PhD candidate will be part of an existing interdisciplinary research team of 5 members:

  • Badrinath Veluri, PhD, Chief Specialist Materials & Material Processing at GRUNDFOS A/S
  • Associate Prof. Devarajan Ramanujan, Head of Section Design & Manufacturing, Aarhus University Department of Mechanical and Production Engineering
  • Assistant Prof. Rami Mansour, Aarhus University Department of Mechanical and Production Engineering

In addition:

  • Two master students at Aarhus University, Department of Mechanical and Production Engineering

Contact

Assistant Prof. Rami Mansour, Aarhus University Department of Mechanical and Production Engineering, ramimansour@mpe.au.dk, +45 93 50 88 67

Deadline

Applications must be received no later than 4 December 2024.

Submit CV & Cover Letter & Grade Transcripts

Please submit your documents before 4 December 2024 here.

PostDoc in Uncertainty Quantification and Stochastic Optimization

PostDoc in Uncertainty Quantification and Stochastic Optimization

Are you interested in uncertainty quantification and optimization under uncertainties? Are you thrilled to work within a multidisciplinary team focusing on the development of novel reliability methods and high-quality research in collaboration with leading research and industrial partners? This is your opportunity to join the research team on a cutting-edge EU-funded research project.

Expected start date and duration of employment

This is a 1.5 year position with possible extension starting from 15th of January or as soon possible thereafter.

Job description:

The EU-funded ACCURATE project aims to boost the competitiveness of European manufacturing companies and value chains by improving their sustainability, performance stability, resilience, and ability to manage unforeseen events. To achieve these benefits, the postdoc project tasks include:

  • Developing a framework for multi-objective optimization under uncertainties for manufacturing services and supply chain networks.
  • Integrate sustainability and circularity metrics into a stochastic optimization loop with constraints on reliability and resilience.
  • Apply reliability- and robustness-based optimization in manufacturing planning in collaboration with leading industrial partners in the ACCURATE project consortium.
  • Collaborate with the ACCURATE project partners to deploy and validate the developed solutions in real-world industry cases.

Who we are

The Design and Manufacturing section at Department of Mechanical and Production Engineering focus on pioneering research with an interdisciplinary approach targeting product development, manufacturing processes, production technologies and value chain optimization.

The PostDoc project will be within the Reliability Modelling & Optimization Lab led by Assistant Prof. Rami Mansour and the Lifecycle Design and Manufacturing Lab led by Associate Prof. Devarajan Ramanujan as well as co-supervised by Associate Prof. Jalil Boudjadar from the Department of Electrical and Computer Engineering. The postdoctoral researcher will be part of an existing interdisciplinary research team of 5 researchers (3 faculty members, 1 PhD, 1 Postdoc) working on the ACCURATE project, between the Mechanical and Production Engineering and Computer Engineering departments at Aarhus University.

Place of work and area of employment

The postdoctoral researcher will be placed in the Department of Mechanical and Production Engineering, within the Design and Manufacturing section, Katrinebjergvej 89, 8200 Aarhus N, Denmark.

Your profile

Applicants should hold a PhD in Engineering, Mathematics or Computer Science with focus on uncertainty quantification and optimization under uncertainties. Knowledge in machine learning, discrete event simulation, and time-dependent reliability analysis will be considered an advantage. It is an advantage if applicants have documented experience in scientific programming, e.g., Python and MatLab. It is required that the applicant is proficient in English, has strong communication skills, and an excellent track record of publishing academic articles in recognized venues.

Contact information

For further information, please contact:

Assistant Professor, Rami Mansour, +45 93 50 88 67, ramimansour@mpe.au.dk

Associate Professor and Head of Design and Manufacturing Section, Devarajan Ramanujan, +45 93 50 88 48, devr@mpe.au.dk

Apply

Applications must be received no later than 3 December 2024.

Please apply here.