实验能源系统研究方向博士职位

Research Associate and Doctoral Candidate (f/m/d) in Experimental Energy System Research

Technische Universität München · 德国

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研究内容
开展实验性能源系统研究,专注于设计和评估创新型、数据驱动及基于机器学习的系统,以整合可再生能源并提高能源使用效率。
申请条件
持有工程相关领域(如电气或机械工程)的高于平均水平的硕士学位,具备实验室硬件规划与建设的实践经验,并拥有极佳的英语能力。
待遇
提供薪酬等级为 TV-L 13 的雇佣职位,初始合同期限为 2 年,并支持攻读博士学位。
申请方式
请于 2026 年 5 月 4 日前将申请材料整合为一个 PDF 文件并通过电子邮件发送至指定邮箱。
材料清单
  • Curriculum vitae
  • Complete academic transcripts
  • Letters of reference
  • Bachelor and Master thesis

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来源
Technische Universität München 官方招聘 · 最近核对 2026-10-07
判定依据(原文摘录)
  • is_phd
    Research Associate and Doctoral Candidate (f/m/d) in Experimental Energy System Research
  • is_phd
    We support your doctoral dissertation in the research area outlined above.
  • english_ok
    Very good command of English
  • bachelor_ok
    Above-average master’s degree in an engineering-related field (e.g., Electrical or Mechanical Engineering)
原文

Research Associate and Doctoral Candidate (f/m/d) in Experimental Energy System Research

27.03.2026, Academic staff

You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research environment? Then let’s design the energy management systems of the future together!

Our research focus: The researchers working at the Professorship of Energy Management Technologies are focusing on the design and evaluation of innovative data-driven and Machine Learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop novel optimization methods, Machine Learning algorithms, and prototypical Energy Management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable future. These EMS coordinate distributed renewable generation like solar and wind, flexible loads like heat pumps and electric vehicles, and distributed energy storage like stationary batteries and hydrogen storage to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation of existing systems, extensive simulation-based analyses, as well as the implementation and validation of algorithm and system designs in real world settings. Your tasks: You will take the lead building our laboratory for intelligent energy management systems. The laboratory's purpose is to provide versatile test facilities for the development and validation of data-driven energy management systems for monitoring and controlling various energy systems. Your work will include planning hardware test facilities, ordering hardware, supervising and participating in the construction of test facilities, developing and implementing safety plans and procedures, designing and conducting experiments, setting up teaching formats (e.g., lab courses) based on the test facilities and experiments, and publishing experimental results in academic venues. Test facilities are planned in the following areas, among others: active distribution networks, energy disaggregation, building thermal control, and distributed prosumer management. The Professorship of Energy Management Technologies closely collaborates with other professorships at TUM, industry partners, and partner research institutions. You will support us in making these cooperations efficient and productive. As Research Associate you will support our teaching activities in several Bachelor and Master programs offered by the School of Engineering and Design and the School of Computation, Information and Technology. You will help us to prepare teaching material, serve as teaching assistant in our lectures, support lab courses, and supervise student research. Your profile: • Above-average master’s degree in an engineering-related field (e.g., Electrical or Mechanical Engineering) • Hands-on mentality with practical experience in planning, constructing, and using lab hardware in the energy systems area • Strong interest in energy technology and systems • Good software engineering • First experiences in control systems and Machine Learning • Inquisitive and passionate about research and knowledge transfer • Independent, creative, and committed way of working • Ability to think conceptually and analytically • Very good command of English • Big plus: good command of German

Our offer: We offer you the opportunity to do research within a team of highly motivated researchers and benefit from the research environment offered by one of the best universities in Europe and worldwide. We support your doctoral dissertation in the research area outlined above. The offered position (pay grade TV-L 13) is initially limited to 2 years. Further employment is possible and intended. Your application: We are looking forward to your application until May 4, 2026. Please submit it as one single PDF file via email to applications.emt@ed.tum.de. Your application should contain the following documents: • Curriculum vitae • Complete academic transcripts • Letters of reference from previous positions held, including internships • Bachelor and Master thesis

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: applications.emt@ed.tum.de

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