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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred
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have earned a PhD degree by the time of appointment, or shortly thereafter. Alternatively, applicants must have a Master’s degree with at least five (5) years of teaching experience. Relevant fields
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in their cover letter. Tier 2 Chairs are intended for exceptional emerging scholars. Nominees should be within ten years of receiving their PhD or terminal degree in their field. Applicants who
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), debuggers, code verifiers and unit test frameworks and gain experience in graphical user interface design and algorithm development. Posting end date: July 11, 2025 Number of positions (est): One (1) position
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, sometimes from multiple jurisdictions, to achieve sample sizes appropriate for training algorithms. This creates challenges with data security and data flows (due to legislative restrictions). Further, data
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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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promising candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks
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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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. While Staff Scientists are expected to have 5 or more years of post-PhD experience, individuals with a relevant Ph.D. and associated expertise can qualify for Staff Research Scientist. The Staff Research
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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