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Field
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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outcomes for children with IBD. The successful candidate must hold a PhD, PharmD or MD/DO with a focus on pharmacometrics or computational biology/bioinformatics focused on -omics with an interest in
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gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing
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required to meet the eligibility criteria. Of secondary importance are: Experience with Python and relevant libraries for machine learning, optimization and simulation. Documented expertise in simulation
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and/or instrument control code, leveraging advances in machine learning and real-time control fabricate robust instrumentation or photonic components for use at 8m-class and future ELT-class
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Research Associate will contribute to developing and/or applying artificial intelligence, machine learning, and image segmentation and/or data science-based methods to address cutting-edge topics, including
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Humanities Scholars Program Postdoctoral Associates Call for Applications: Humanities Scholars Program Postdoctoral Associates Open to Cornell PhD Candidates and Recent Cornell PhDs Eligible
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have demonstrated experience applying AI and machine learning tools to manage, clean, and code complex nutrient content and food product datasets. Experience with data visualizations, front of pack
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and deliverables. Learn background/research methods of studies for which analysis is conducted with limited direction and supervision. Statistical analysis and database management. Conduct systematic