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Field
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Scheduled Hours 40 Position Summary We are assembling a team of Computational Biologists to answer important questions about neurodegeneration, organelle biology, and context-dependent gene function
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the prevalence and risk of modern slavery. There will be a focus on Bayesian nonparametric methods and practical development of MCMC algorithms that can be applied to data. Translating the project findings
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algorithm. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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learning. At least five (5) years of experience in AI/ML/DL or equivalent combination of education and experience. Demonstrated experience in algorithm development and structured programming ability
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and financial planning tools; this includes modeling new algorithms, creating functional specifications, and testing and/or validating new financial planning tools. Collaborate with other members
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creating data algorithms and specialized computer software to identify and classify components of a biological system (i.e. DNA and protein sequences). Applies basic application of computational tools and
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of Chicago Law School. Responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting