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Field
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experience using Python machine learning and large language models. Experience in machine learning and NLP for automated misinformation detection, social media data scraping and analysis, and human annotation
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. The candidate will also have experience of psychophysiological methods, preferably EEG or MEG, and strong quantitative and programming skills in time series analyses using Python/MATLAB (or equivalent
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from Non-Destructive Testing methods, Interferometric Synthetic Aperture Radar (InSAR) or similar, using software tools such as MATLAB and Python amongst others. Prior hands-on experience in optical
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R and Python and AI software and a willingness to adopt new technologies will also support your success. If you're passionate about research that informs better science and you're ready to contribute
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publications. It involves conducting systematic reviews and working with analytical software such as R or Python, with a focus on both independent and collaborative research. The role also requires experience in
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statistical / data science languages such as R or Python Experience working with geographic information systems Desirable Characteristics: Experience with building spatially explicit models, including
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experience with analytical software like Stata, R, or Python, are essential. The ideal candidate will also have experience with geospatial tools. Additionally, you will have experience designing and managing
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and instrumentation. Familiarity with design and simulation tools like SolidWorks, Autodesk Inventor, MuMax, OOMMFi COMSOL, or similar. Familiarity with the programming languages Python, Matlab
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community. Requirement: PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C++, or Go, and frameworks like
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experience in programming languages such as R, Python, and familiarity with NLP tools and techniques (essential) Proven track record in handling and analyzing large healthcare dataset (essential) Track record