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and computer scientists PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust
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Science, Machine Learning, Computational Linguistics or a related field, if applicable with PhD previous experience in Natural Language Processing, knowledge Graphs, Machine Learning or Recommender Systems
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performance, yet their atomic-scale origin and role in reactivity remain poorly understood. The project addresses this open problem by integrating high-throughput Density Functional Theory, machine-learning
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candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically
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to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
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identification, optimization, or numerical methods is valuable, as is knowledge of data analysis and machine learning for complex, high-dimensional systems. Programming experience in MATLAB or Python, and an
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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experience Practical experience in machine learning and the application of large language models Knowledge of OMICS and image data analysis A willingness to engage in interdisciplinary scientific work
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machine learning models. Working with extremely large, multi-modal datasets. Prior experience in analysis of clinical health records, and time series data are highly preferred. Qualifications Requirements
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. or Diploma in bioinformatics or a comparable qualification Extensive programming experience Practical experience in machine learning and the application of large language models Knowledge of OMICS and image