610 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"SUNY" Postdoctoral positions in United States
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Field
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regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. The Postdoctoral Associate will conduct research in statistical machine learning and
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original research on clandestine printing networks using computational tools Contribute to publications in both AI and humanities venues (machine learning conferences and book history journals) Contribute
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years of post-degree experience. Applicants should address how they would contribute to the research focus of Math+AI. The primary focus of this position is in creating methods and applying Machine
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necessary to become credentialed as a Principal Investigator Applying a broad range of statistical and machine learning methods to human performance data collected in real-world settings Developing
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Integrate multi-omics data with clinical, cognitive, and imaging phenotypes in longitudinal cohorts Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival analysis
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-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference
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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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Biology with both high-throughput experimental (proteomics and genomics) and integrative computational (network analysis and machine learning) methodologies, aiming to understand gene functions and their
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methodologies: optogenetics, calcium imaging, viral tracing, tissue clearing, murine behavioral phenotyping, machine-learning behavioral analysis Familiarity with programming languages (e.g. R, Python) and an
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candidates will have strong past experience in scientific machine learning. Experiences in large language models, molecular modeling and simulations, and/or polymer science are preferred but not required