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. Physical Review Research, 2, 043217, 2020). You will use our mature simulation code to carry out simulations. Knowledge of a python framework for machine learning is essential (e.g. TensorFlow), as is
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Organization U.S. Department of Defense (DOD) Reference Code USAISR-2025-0004 How to Apply Click on Apply at the bottom of the opportunity to start your application. Description The U.S. Army
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sequencing, proteomics and lipidomics, functional assays, and microscopic imaging. Mastering all of these techniques is not necessary, as the project will be carried out in collaboration; however, there is an
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Krios microscopes, all hosted and maintained at ETH Zurich’s imaging facility, ScopeM. Appropriate computational resources are also readily available. In addition, we have access to the biophysical
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. [4] Sivakumar et al., Phys. Rev. B 111, 075409 (2025), Influence of surface relaxations on scanning probe microscopy images of the charge density wave material 2H-NbSe2. [5] B. Kiraly et al., Nano Lett
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have experience in routine molecular biology techniques like Western blotting, PCR, immunohistochemistry and/or microscopy. Experience with electrophysiology or live-cell imaging techniques like calcium
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 3 months ago
contribution to our focus project of realizing online-adaptive proton therapy, enabled by an AI driven, fully automatized feedback loop of imaging, PGI-based treatment verification and fast adaptation. Therefore
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science, conservation science and planning, or a closely related field at the time of appointment. Preferred qualifications ● Coding fluency in R, Stata and/or Python for statistical analyses; ● Excellent
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of individual Milky Way-like galaxies Programming in Python, C/C++ and/or Fortran, and experience in parallel code development Experience in the development and use of tools for analysis of output of hydrodynamic
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assess their usefulness. Co-create a regional risk picture by facilitating workshops to prioritise event–disruption–risk combinations with compounding impacts on care (e.g., precipitation extremes