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, or academic projects • Experience in writing research code in collaborative settings using languages such as R and Python • Ability to work effectively as part of a multi-disciplinary research team • Strong
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, or other real-world data sources. Proficiency in R, SAS, Python, Stata, or similar analytic software. Demonstrated experience contributing to manuscripts, scientific abstracts, reports, or grant applications
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generator code, C++, Python. Excellent verbal and written skills. Presentation skills. Analytical skills. Attention to detail. Salary: Compensation will be commensurate based on the selected candidate's
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relevant programming language (e.g., R or Python). Strong written and oral communication skills. Experience managing multiple projects at once. Willingness to learn new technical skills and gain knowledge in
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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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science related discipline. You will possess established expertise in data analysis including statistical programming (e.g., STATA, RStudio, Python). You will demonstrate previous experience of contributing
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. Integration of physiologic waveform features with clinical metadata and outcomes. Creation of reproducible Python and/or MATLAB pipelines for clinical signal processing and analysis. Translation
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or equivalent approaches. Automated experimental testing, instrument control or data acquisition using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is
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including transformers, self-supervised learning, foundation models, autoencoders or related architectures; strong programming skills in Python and experience with a deep-learning framework such as PyTorch
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scientific programming in Python and the use of frameworks such as PyTorch or TensorFlow. It is also necessary to have experience in federated learning and deep learning applied to medical imaging, as