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Field
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modeling. Proficiency in Python and experience with AI/ML frameworks such as PyTorch or TensorFlow. Experience handling large geospatial, atmospheric, or remote sensing datasets is preferred. Strong
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will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python
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skills (e.g., Python) implementing computational analytical pipelines and familiarity with machine-learning frameworks are required. The post is full-time 35 hours per week, 1.0 FTE and fixed term for 19
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, computer science, physics, data science or a closely related discipline. • Experience in MRI image analysis and scientific programming, preferably using Python and modern computational libraries. • Experience
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reports. Job Requirements: PhD in Physics, Applied Physics, Plasma Physics, or related field. Demonstrated experience in scientific computing and numerical modelling (e.g., Python/C/C++/Fortran). Experience
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, delamination, metastability effects) Identify gaps and contradictions in reported degradation knowledge and formulate hypotheses that connect findings across studies Develop data analysis procedures (Python
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, or fibre-based optical clock comparison and dissemination. Experimental automation Python-based experiment control, FPGA or ARTIQ sequencing, and real-time digital feedback for clock servo loops.
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methods for additive manufacturing applications, including ANNs and evolutionary genetic algorithms for process optimization supported by programming knowledge (e.g. Matlab, Python). Hands-on experience
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polarization states. • Data Analysis & ML: Develop Python/MATLAB machine learning algorithms to map photocurrents to full Stokes parameters, targeting a reconstruction error of \(<1\%\). Required
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such as space, aviation, automotive, rail or medical; experience with data analysis and modelling tools, such as Python or MATLAB, including handling of datasets used for training, testing and validation