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computing (Linux) environments, including shell scripting. Strong programming and data analysis skills (e.g., Python, Fortran, R). Demonstrated ability of scholarly output (peer-reviewed publications and
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models and/or probabilistic modelling, and excellent programming skills in Python and a modern deep learning framework (e.g., PyTorch or JAX) are required. Excellent skills in spoken and written English
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experiments Demonstrated ability to analyze experimental data (e.g., in Python, MATLAB, or equivalent) KEY RESPONSIBILITIES AND ACCOUNTABILITIES 1. Design, perform, and analyze nanoscale magnetic resonance
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, for example using Python or comparable tools, and experience with GIS-based spatial analysis. The ability to work with heterogeneous geological, hydrogeological and monitoring datasets and to connect
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-precision photometry and/or time-series analysis. Research experience in observational astronomy, demonstrated through publications appropriate to your career stage. Solid programming skills (e.g., Python
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to autonomous systems is considered an asset. Proficiency in relevant programming and simulation tools, such as Python, C/C++, MATLAB/Simulink, ROS/ROS 2, Gazebo, AirSim, or equivalent platforms. Experience in
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publications in the field. Required skills include operation and alignment of custom laser instrumentation, and programming experience in e.g. MATLAB/Python/LabVIEW for data analysis and software experimental
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instrumentation. Experience with Python, model/API integration, retrieval-augmented generation, tool-using agents, scientific databases, and automated experimental platforms is highly desirable. The candidate is
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microscopy, optogenetics, or in vivo imaging techniques. Experience with electrophysiological recording methods, including patch-clamp techniques. Programming and data analysis experience using MATLAB, Python
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Engineering, or a closely related quantitative field is required. Additional qualifications The candidate must have strong programming experience in Python and/or R. The candidate must have experience analyzing