68 parallel-computing-numerical-methods "Institute of Computer Science" Postdoctoral positions at Cornell University
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research project in any of several areas relevant to this topic, and to explore multiple lines of research in parallel. Most projects employ a combination of bacterial genetics, high throughput genetic
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to this topic, and to explore multiple lines of research in parallel. Most projects employ a combination of bacterial genetics, high throughput genetic screens, biochemistry, ribosome profiling (ribo-seq
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, operations research, or statistics). An ideal candidate would have proficient programming skills and demonstrated experience in computational modeling (particularly integrated assessment or power systems
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biofluid samples Conceive, prototype, and benchmark new computational and AI methods for liquid biopsy, including techniques to bridge to other data modalities, e.g. imaging Apply modern machine learning
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approaches, including machine-learning methods, that improve the identification or enumeration of overlapping vocal individuals. Array localization, spatially explicit capture-recapture, distance sampling
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, computational methods and theories for humanistic and social scientific inquiry, and the ethical, political, or historic dimensions of artificial intelligence but we will consider outstanding applicants working
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unique combination: deep expertise in molecular and computational biochemistry (Moghe Lab; https://www.moghelab.org ) paired with field-tested ecological and evolutionary chemistry (Agrawal Lab; https
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studies will also be considered. Computational methods, content analysis, surveys, and other methods can be used complementarily, but should not be the primary method. Viable path towards access
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probabilistic models, hybrid numerical approaches, computational algorithms, and integrated software platforms for modeling and managing the interactions among urban infrastructure and environment networks
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, biological sciences, computer science, machine learning) Demonstrated quantitative skills, including proficiency in programming (R and/or Python) Previous experience developing statistical methods or working