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the code “CNTR_25.2” (e.g. “Mustermann,Max_CNTR_25.2”). Please note that there is no application deadline for this application process. Applications will be reviewed in an ongoing manner until
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85748, Germany [map ] Subject Area: Physics / HEP-Phenomenology (hep-ph) Appl Deadline: 2026/01/31 11:59PM (posted 2024/08/04, listed until 2026/01/31) Position Description: Apply Position Description
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array of topics in the focus areas of energy, infrastructure, environment, materials, and chemistry and process engineering. The advertised position is part of the newly founded division 4.2 ‘Material
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of the application and selection process, please refer to the privacy policy on our homepage at https://www.senckenberg.de/en/imprint/ Please visit our website at www.senckenberg.de for further
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, materials, and chemistry and process engineering. We are looking for talented people to join us. Your responsibilities include: Further development of laser ablation inductively coupled plasma mass
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | about 2 months ago
interaction for chemistry and materials. Overall, we aim to unravel and apply fundamental physical principles to create and control novel states of matter with light. For the ERC Synergy project “Unravelling
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. The position is for at least 12 months, starting at the earliest opportunity. Applicants should hold a PhD or equivalent in Materials Science or Physics. Experience in some of the following areas would be highly
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preferential consideration if they are equally qualified. The advertised position requires a low level of physical aptitude. BAM actively supports the compatibility of work and family and has been certified as a
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Science, Mechanical Engineering, Materials Physics, or a closely related field A strong academic track record and a solid understanding of the mechanical behavior of materials and materials science Hands
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theoretical ecology, geosciences, applied mathematics, environmental physics, or a related field. Research experience in numerical modelling, preferably with knowledge of either eco-evolutionary models and/or