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Field
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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tools such as SPM, FSL, AFNI, and/or DSIStudio etc will be an advantage. Signal processing and programming skills (e.g. with Matlab, Python) will be an advantage. Ability to use statistical packages
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. If necessary, the applicant selected for the position will be trained in indoor localization. § Good computing skills and proficiency in some programming languages, such as C/C++ and Python, and MATLAB is
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, in addition to, optimisation of data processing and statistical analysis pipelines and writing of custom MATLAB scripts for signal analysis. Prior experience in neuroimaging and/or electrophysiology
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Physics, Electrical Engineering, Materials Science, or a related field with low-dimensional nanophotonics. Excellent publication records will be preferred. Experience in matlab, MEEP, RCWA and other
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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data
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discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning
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. • Proficiency in programming (e.g., Python, C/C++, MATLAB) for model development and data analysis. • Demonstrated ability to work independently and as part of a multidisciplinary team
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(e.g., carbon, nutrients, oxygen) or transient tracers such as CFC-12 and SF6, is required. Proficiency in MATLAB or Python is required. Applicants must be able to take part in a nearly two-month-long
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simulation for physical systems. Strong foundation in mathematical modeling, simulation and quantum mechanics. High proficiency in scientific programming (Python, C++, MATLAB, or similar), with experience in