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statistics, engineering physics, physics, machine learning, or in a similar subject, or have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including
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computer science, image analysis and machine learning, engineering physics, data science, applied mathematics, molecular biotechnology engineering, or another related field; or Have completed at least 240
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background in Machine Learning, with the ability to understand and extend current research Solid programming and engineering skills Comfortable working with modern development tools and practices Strong
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, engineering physics, physics, machine learning, or in a similar subject, or have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including an independent project
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta