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Classification Title: Post Doctoral Associate Job Description: The Department of Epidemiology (http://epidemiology.phhp.ufl.edu/) is strategically situated within the College of Public Health and
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
applicant will contribute to the AIGLE project by: · Developing innovative scientific Deep Learning/Machine Learning algorithms for flash flood forecasting. · Contributing to the collection
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the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility. Competitive wages, paid holidays, and generous time off Continuous learning opportunities through
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Informatics, Health Data Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated
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related to creating or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Basic Qualifications Core job duties include
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at the intersection of mathematics and AI safety, with a focus on developing rigorous mathematical foundations for AI interpretability. Research directions include mean field theories of deep learning, data attribution
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of Artificial intelligence for De-Novo molecular design Machine learning/Neuronal networks to develop novel drug discovery tools Molecular modeling and simulation Theoretical biophysical medicinal chemistry Deep
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical
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institutions of the distinguished Association of American Universities. Connections working at New York University More Jobs from This Employer https://main.hercjobs.org/jobs/22080154/postdoctoral-associate
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opportunity to field test and validate their methods using real-world systems. Postdoctoral fellows will work across the following research areas: Predictive machine learning Robust and stochastic optimization