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quantitative skills (R, Python, or Stata; experience with machine learning or advanced experimental methods is a plus). ▪ Familiarity with VR-related toolkits (e.g., Unity, Unreal, or eye tracking) is an
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methods You will work closely with: - Dr. Martin Ramacher (machine learning for environmental applications) - Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a project
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spatial omics data and to uncover the regulatory mechanisms driving cellular differentiation during vertebrate embryonic development. In this project, you will develop quantitative machine learning models
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Research Engineer or Postdoctoral Researcher (m/f/d) in the field of Engineering Physics or Material
engineering A completed Master’s degree or PhD in Engineering Physics, Materials Science, Engineering or a similar discipline The ability to work independently, a willingness to learn, and a team spirit Good
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22.12.2025, Academic staff We are an interdisciplinary team at the Chair of Safety, Performance and Reliability for Learning Systems, and we are looking for exceptional postdoctoral researchers
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independently while contributing effectively within a multidisciplinary team Please feel free to apply for the position even if you do not have all the required skills and knowledge. We may be able to teach you
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Master’s degree or PhD in Engineering Physics, Materials Science, Engineering or a similar discipline The ability to work independently, a willingness to learn, and a team spirit Good English skills
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international journals • Present research findings at international conferences • Teach courses and supervise theses in the field of supply chain management • Support third-party funding applications Your profile
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, for event reconstruction and classification, including potentially machine learning/AI Interpretation in suitable theoretical models Contribution to software activities that are required for wider use by DESY
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Helmholtz Association of German Research Centres | Oldenburg Oldenburg, Niedersachsen | Germany | 2 months ago
of these areas, a willingness to expand into the others, as well as a general interest in sustainability. They will be proficient in quantitative methods such as causal inference, machine learning, and simulation