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variety of perspectives enrich our work and our daily collaboration. In a continuous process of learning and reflection, we aim to ensure that all our employees can be themselves and feel a sense of
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14 Mar 2026 Job Information Organisation/Company Helmholtz-Zentrum Berlin für Materialien und Energie Research Field Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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24 Jan 2026 Job Information Organisation/Company Deutsches Elektronen-Synchrotron DESY Research Field Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application
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position (m/f/d) in multiscale, multiphysics, mathematical modelling of plant morphogenesis as soon as possible. Description of the project Plant growth is a complex hydromechanical process in which cells
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Your Profile: Basic qualifications: Completed Master’s degree with subsequent PhD in Physics, Chemistry, Material Science or related disciplines Experience with neutron spectroscopy (e.g. INS, QENS, NSE
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101118911 Is the Job related to staff position within a Research Infrastructure? No Offer Description The RADES Group at the Max Planck Institute for Physics (MPP) in Garching invites applications for a
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
learning. It also offers the opportunity to work with data from the European XFEL facility at DESY. Project website Your profile Eligible candidates have strong skills in computational physics and
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of Molecular Cell Biology and Genetics (MPI-CBG), the Max Planck Institute for the Physics of Complex Systems (MPI-PKS), and the Technische Universität Dresden (TUD), and a stimulating and inspiring atmosphere
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molecular qbit control. Requirements: University degree (Master or equivalent) in Physics or (Physical) Chemistry and doctoral degree. Desirable: Strong knowledge in the application of EPR spectroscopy and at
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for emulating high-resolution process-based land-surface models - Combine process-based land surface and vegetation model components with data-driven model parts, e.g. in the framework of Neural Differential