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Jun 2025 Financing yes Type of Position Full PhD Working Language English German Required Degree Master Areas of study Automation Technology, Mechatronics, Robotics, Systems Engineering, Applied
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quantification, model-order reduction, or multi-fidelity methods. The primary fields of application are life science, medicine and health, earth observation and robotics. Consequently, a MUDS student will learn
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for anaerobic lab work. See www.tu-dresden.de/bio/mikdiv for background on the working group and on the topic. Requirements: university degree (Master or Diploma or comparable) in Biology or related
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of requirements and scientific literature research Evaluation of the developed methods Preparation of scientific publications Recruitment requirements: Scientific university degree (Master) in computer science or a
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the federal administration. Your Profile Required: Master Degree (or equivalent) in Economics or a related field Proven expertise and interest in industrial policy research Fluent in English (C1
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must include: A cover letter motivating your application. Four presentation slides about your master thesis or another research project of you (1. Motivation and Goal of the research project, 2. Methods
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partners at Princeton and Chicago Present findings at international conferences and co-author publications in high-impact journals Qualifications Master's degree in Physics/Physical Chemistry with excellent
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possible). Equal opportunity is an important part of our personnel policy. We would therefore strongly encourage qualified women to apply for the position. Your tasks The primary task of the project is to
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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI