163 computational-physics "https:" "https:" "https:" "https:" "Caltech" positions at Forschungszentrum Jülich
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is located: https://www.fz-juelich.de/en/pgi/pgi-7/research-groups-1/ag-gunkel-1 Your Profile: Completed qualification to enroll for the Master thesis in Physics, Materials Sciences or Chemistry, with
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geophysics, physics, geoscience, computational geoscience, or related natural sciences with an overall grade of at least good Experience in programming (e.g., MATLAB, Python, C/C++) Advanced knowledge
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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program the memristors Operando characterizing the device electrically and morphologically using conductive atomic force microscopy (C-AFM) Access and active control of advanced experimental setups Your
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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to make them usable for transparent energy system analyses. You will process and semantically enrich the collected data before it is integrated into a knowledge-graph-based metadata platform. In
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: https://go.fzj.de/equality and on specific support options: https://go.fzj.de/womens-job-journey
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or more of the following areas: + Quantum computing and quantum algorithms + Solid-state physics, computational materials science, or quantum chemistry + Battery materials modeling Excellent
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areas: + Quantum computing and quantum algorithms + Solid-state physics, computational materials science, or quantum chemistry + Battery materials modeling Excellent programming skills (e.g., Python) and
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computational engineering, mathematics, computer science, physics, engineering or a related field Strong background in numerical methods and machine learning Proficiency in at least one programming language