研究助理/博士生：储能优化与高性能计算

Back to News Board Browse in News Research Associate/ Doctoral Candidate (m/w/d) for Project “Storage as a Sustainability Enabler through Optimization, Machine Learning and High Performance Computing” 25.09.2026, Academic staff The Institute of Advanced Study (IAS), together with the Professorship of Energy Management Technologies, is offering a Research Associate/ doctoral candidate position as part of a project entitled "Energy Storage as an Enabler of Sustainability through Optimization, Machine Learning, and High-Performance Computing," supported by the Dieter Schwarz Foundation through a Courageous Research Grant. The project is led by IAS Fellow Prof. Anthony Papavasiliou. Research will focus on the application of operations research in power system operations and electricity market analysis, with a specific focus on the funded proposal “Storage as a Sustainability Enabler through Optimization, Machine Learning and High Performance Computing”. Description of the position: The main activity of the researcher will be to conduct research under the supervision of Professor Anthony Papavasiliou (NTUA), recipient of the TUM-IAS Dieter Schwarz Courageous Research Grant. Professor Christoph Goebel (TUM) will act as the host at TUM. Possible topics of research include, but are not limited to • Exploiting GPUs for large-scale optimization • Value stacking of storage in competitive wholesale electricity markets • Optimal planning of electric power systems For more information on the research group of Professor Papavasiliou, interested applicants are encouraged to consult the following link: https://ap-rg.eu/ The researcher will contribute to teaching activities at TUM. The position is for one to three years and carries monthly salary with full benefits (according to TVL-13). Required qualifications: The ideal candidate should hold a degree in Electrical Engineering, Computer Science, Operations Research or a related field. The ideal candidate should have a solid background in optimization, computer science, mathematics, statistics, economics, or related disciplines, an interest for the application of operations research in energy systems and strong programming skills. Familiarity with parallel programming is highly desirable. Proficient knowledge of English is highly desirable. A background in power systems is desirable, though not required. Your application: To inquire about the vacancies, please contact Professor Papavasiliou with a CV. If openings matching your background are available, you will be asked to submit a full application. Full applications should include: • A CV • Unofficial transcripts of undergraduate and graduate studies • Letters of recommendation (references can email their recommendation letters to papavasiliou@mail.ntua.gr) • Samples of academic work Applications and questions about the opening can be emailed to Professor Anthony Papavasiliou at papavasiliou@mail.ntua.gr. Application deadline is Oct 11, 2026. 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: papavasiliou@mail.ntua.gr Print

Required qualifications: The ideal candidate should hold a degree in Electrical Engineering, Computer Science, Operations Research or a related field. The ideal candidate should have a solid background in optimization, computer science, mathematics, statistics, economics, or related disciplines, an interest for the application of operations research in energy systems and strong programming skills. Familiarity with parallel programming is highly desirable. Proficient knowledge of English is highly desirable. A background in power systems is desirable, though not required.