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AI to predict safety outcomes for multiple targets and combination therapies Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods
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majors combined with other majors, and over 100 PhD students. The College of Science and Physics Department are in a vibrant expansion phase. The Department of Electrical and Computer Engineering (https
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Your Job: In this position, you will be an active member of the SDL “Fluids & Solids Engineering” and will collaborate strongly with the SDL “Applied Machine Learning”. You will have the following
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scientists, and technology innovators. Located in the heart of Las Vegas, the College serves a diverse student population and offers robust programs in electrical and computer engineering, computer
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infrastructure (e.g. Observatorio del Roque de los Muchachos) Hands-on training in cutting-edge techniques, from detector R&D to advanced data analysis and machine learning. Attendance to international
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Science About the project This PhD project integrates pharmacoepidemiology, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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Translation; practical experience conducting data-driven research in a machine translation/large language models (LLM)-related area using a variety of technologies, including eye-tracking; experience as
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of Spanish (not required but valued for teaching and policy dissemination in Spain). Experience with AI-based research workflows, machine learning techniques applied to financial data, or modern
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strong AI focus; a PhD is desirable, but not mandatory Advanced knowledge of machine learning, statistical modeling, and modern AI methodologies Strong programming skills, preferably in Python and common