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Field
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datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly
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tools (STATA, R, or Python). Assist in literature reviews and summarising academic research. Contribute to writing research papers and policy reports. Participate in meetings with collaborators and
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and informatics skills are required, i.e., R, Python, MATLAB, deployment of web experiments (using cloud services). Being able to communicate fluently in English is a must. Your future tasks: As a new
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quantitative data analysis. Proficiency in programming (e.g., JavaScript, Python, React for iOS/Android) is important. Additional strengths would include experience with physiological sensing (e.g., EEG
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Master’s degree in physics, mathematical biology, computational biology or a related subject. They should have good skills in programming languages such as Python, MATLAB or R, and experience in image
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., TensorFlow, PyTorch) and transfer learning models. Proficiency in Python programming and handling medical image datasets. Strong understanding of computer vision, CNNs, and attention mechanisms. Experience
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or machine learning. Excellent programming skills (e.g., MATLAB, Python, or ROS), a strong publication record, and an ability to work collaboratively in multidisciplinary environments are essential. Prior
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High-level analytical capability Ability to communicate complex information clearly Experience in COMSOL Multiphysics, Coventorware, Matlab and Python and Autodesk Fusion360 Experience of working with
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Epidemiology or related subject or a similar quantitative discipline. Programming skills in Python; or experience in at least one of the following: C, C++, Java, R, Matlab, and willingness to learn Python
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: C1 Proficient in programming using Python, and deep learning frameworks such as TensorFlow and PyTorch. C2 Research creativity and cross-discipline collaborative ability as appropriate. C3 Excellent