Fully Funded PhD Position in PDE-based optimization of deep geothermal systems

Location: Germany
Application Deadline: Open until filled
Published: 1 month ago

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The Chair of Renewable and Sustainable Energy Systems (ENS) at the Technical University of Munich (TUM) deals with the modeling and optimization of energy systems on different temporal and spatial scales. For our new Research Group Applied Optimization we are looking for a Research Associate: PDE-based optimization of deep geothermal systems starting immediately, in full-time.

The Chair of Renewable and Sustainable Energy Systems (ENS) at the Technical University of Munich (TUM) deals with the modeling and optimization of energy systems on different temporal and spatial scales. For our new Research Group Applied Optimization we are looking for a Research Associate:

PDE-based optimization of deep geothermal systems

starting immediately, in full-time.

Research topic:

Deep geothermal energy is one of the key technologies to decarbonize the heating sector. To enable efficient, reliable and sustainable use of deep geothermal well doublets, it is essential to optimize them (location, sizing, operation, etc.). The resulting optimization problems are the so-called PDE-constrained optimization problems, since the physical processes in the underground are governed by PDEs. To efficiently solve these mathematically challenging problems, new optimization approaches need to be developed.

Tasks:

  • Work in a team on a national collaborative research project, which deals with the development of a planning and optimization tool for deep geothermal systems.
  • You will be responsible for developing solutions in terms of methodology (optimization approaches) and implementation of the optimization tool.
  • Coordination of the cooperation with the project partners
  • Publication of results in peer-reviewed journals and presentation at international conferences
  • Contribution to the education of students and thus support of our educational mission.

Requirements:

  • Above average Master’s degree in engineering, applied mathematics or computational science
  • Good knowledge of mathematical/numerical optimization methods
  • Strong mathematical skills and interest in developing new mathematical methods
  • Enthusiasm for challenging mathematical problems and interdisciplinary collaboration
  • Relevant experience with programming languages (preferably Python)
  • You work independently, in a structured and reliable manner.
  • You are communicative, flexible and able to work under pressure.
  • Fluency in English language (writing/speaking)
  • German language skills are an advantage.
  • Applicants who are already pursuing or hold a doctorate will be automatically disqualified

We offer

  • An interesting and challenging job in an international and dynamic team at TUM’s Garching site
  • Flexible working hours
  • Individual opportunities for further training
  • Employment in accordance with the collective wage agreement for the civil service (TV-L E13)
  • Pursuing a doctorate within the framework of the work at the TUM

People with a severe disability will be given preferential treatment if their suitability and qualifications are essentially the same. TUM aims to increase the proportion of women, so applications from qualified women are expressly welcomed.

Interested?

Then we look forward to receiving your application; please send them by e-mail to jobs.ens@ed.tum.de with “PhD application – Optimization” in the subject. Please include the following documents as a single PDF file titled “PhD_Optimization_YourFirstName_FamilyName”: detailed CV (including publications if applicable), cover letter, full academic transcript (Bachelor and Master), MSc thesis summary. If you have any further questions, please do not hesitate to contact Mr. Smajil Halilović (smajil.halilovic@tum.de). The position remains open until filled (Review begins in mid-March).

 

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: smajil.halilovic@tum.de

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