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areas: -developmental biology -experimental and/or theoretical biophysics -experimental and/or computational genomics -computer science, statistics, and/or machine learning with applications relevant
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proposals. Responsibilities Develop, implement, and evaluate new statistical and machine learning methods aligned with the two themes above. Lead and co-author manuscripts in statistical, machine learning
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) and genetics data which are measured by longitudinally and cross-sectionally. • Developing and applying machine learning and AI approaches to identify interactive topological relationships
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Monitoring Drift Chambers (MDT), and in the Event Filter track trigger (EFTracking). The group applies novel Machine Learning tools and techniques to both analyses and trigger upgrades, and leverages FPGA and
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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factors. Though not required, we are particularly interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and
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Appointment Term: Initially 1 year, renewable Appointment Start Date: Fall 2025 but flexible Group or Departmental Website: https://www.liwanglab.org/ (link is external) How to Submit Application Materials
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Science, Computer Science, Data Science, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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education. Connections working at Princeton University More Jobs from This Employer https://main.hercjobs.org/jobs/21923150/2025-postdoctoral-research-associate-ai-machine-learning-for-analytical-and-forensic