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to or even much larger than the total sample size n. We refer to such “large p, small n” data as high-dimensional data. An enduring interest in statistics is to compare the covariance matrices of two high
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, Public Health, Climate Science, Data Science, or related disciplines. Demonstrated experience in managing large-scale data sets and conducting health-related research studies. Strong analytical skills with
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agentic architecture. With prior experience in AI security and AI agents, including prompt injections, data extraction, jailbreaking, poisoning and adversarial attacks, the candidate brings transferable
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synthesis of novel functional materials. Key Responsibilities: Implement data processing pipelines for materials informatics, including large-scale data mining, curation, and processing. Integrate
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. Technical Skills: Proficiency in medical statistics, data science, and applications across various domains. Skills in processing and analyzing large datasets, data wrangling, visualization, big data analysis
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++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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with a big dream. We are home to the best talent and have the world’s highest per capital investment in science and technology. Key Responsibilities Collaborate with partners from both the academia and
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outputs across Projects 3-1 and 3-2 Manage and process large sets of operational data for case study analysis Contribute expertise in power grid optimisation to enhance planning models Participate in
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with time-series data. The role involves conducting research on multimodal learning and leading technical development efforts within the project. Qualifications Applicants should meet the following