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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
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of thousands of molecules in our fully automated high biosafety screening facility CAPS-IT against multiple viruses. You will be responsible for the development and deployment of advanced machine learning models
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and machine-learning potentials for planetary materials. Curating and generating large-scale ab initio datasets across wide pressureâ“temperature regimes. Designing and training advanced machine
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intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and scientific applications. About the research project You will work in Julian Togelius' new research
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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Experience in plant breeding for resistance to biotic and/or abiotic stresses, programming, machine learning, and genomic data analysis. Desirable requirements 1. Cost-effectiveness assessment: rapid
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-cell or spatial transcriptomic analysis is desirable. Experience with machine learning, LLMs, AI agents, multimodal data integration, or automated biological interpretation workflows is desirable but not
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, machine learning, and data science. The successful candidate will work with Dr. Yohanna Mejia Cruz on the development of sensing and computational frameworks to characterize human mobility and behavior
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. Unsupervised machine learning approaches will be used to identifiy key dimensions of circadian rhythm associated with dementia subtypes. This requires a very good level in statistics and R programing as
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Link https://www.ubjobs.buffalo.edu/postings/63869 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting Detail Information Position