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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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of inorganic ions and organic matter can cause defects in electrolyser stacks, resulting in costly process disruptions. This project considers: i) development of analytical methods for the quantification
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it is the working language of the lab. Desired skills Experience with analytical chemistry (LC/MS, GC/MS) and behavioral assays Experience with animal husbandry and colony maintenance. The Research
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, storage, accessibility/sharing, archiving, publication, and preparing data for machine learning applications. The Research Training Group RTG 3120 offers, subject to the availability of resources, a
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Areas of study Neuroscience, Physics, Applied Computer Science, Bioinformatics, Computer Science, Engineering Informatics, Medical Informatics, Chemistry, Analytical Chemistry, Inorganic Chemistry
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presentation and publication of the results Requirements: university degree (Master's or equivalent) in geodesy or a related subject (geophysics, geoinformatics, physics, mathematics) excellent analytical skills
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well as analytical methods are an advantage Willingness to handle unsealed radioactive materials within a radiation-controlled laboratory environment Knowledge of handling radioactive materials and radiochemical
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research proposal required for application with a timetable for the four-year research project. Required equipment will be set up and further development of relevant analytical methods will follow
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-motivation and interest to learn new skills Great to have: Experience programming in Python, Julia, or C/C++ Experience with Mathematica Experience with finite element methods, agent-based simulations, and/or
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. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and