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Field
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, there are no such drugs. This leaves also critical gaps in epi- and pandemic preparedness. Antiviral drug discovery efforts typically focus on a few known targets. Yet, the biology of viral replication consists
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help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
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and efficiency of life sciences research. Developing the algorithms, infrastructure, and governance necessary for such analysis can simultaneously enhance hypothesis generation, computational modeling
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. Developing the algorithms, infrastructure, and governance necessary for such analysis can simultaneously enhance hypothesis generation, computational modeling, and post hoc support for laboratory studies and
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disease areas. Preference will be given to applicants with prior training in Computer Science, Computational Biology, Computational Chemistry, and Computational Biophysics. Extensive training opportunities
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, including bioacoustics algorithms developed in the team. What you will do Conducting rigorous research at the intersection of ML and wildlife bioacoustics; Actively participating in regular group and one
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mathematics, or physics to apply their expertise to challenging problems in computational imaging, while collaborating with leading experts in physics, biology, and environmental science. Research Context Soil
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in biological and/or medical science, computational biology. Experience with R/Python programing and machine learning algorithms. Familiar with genome, genome sequencing, genome transcription
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. Experience and PhD in Neuroscience, Computational Biology, Computer science, Statistics, Mathematics, or related fields. Key Responsibilities: Collaborate in Electrophysiological Data Acquisition and
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Develop event-driven algorithms and software components for autonomous experiment control and adaptive image acquisition Build scalable, maintainable, and open-source software for high-throughput image