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performing theoretical DFT calculations for solid-state systems and lattice dynamics calculations applying machine learning techniques to predict the solubility of pharmaceutical cocrystals supervising and
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include responding to inquiries, managing appointments and reimbursements for Postdocs and Visitors, and serving as a liaison with various stakeholders. This role will also handle appointment processing
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to maintain detailed records of experiments and outcomes. General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications. Ability to work
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of molecular data at cellular resolution, opening new avenues for the application of machine learning to fundamental biological problems. The postdoc (M/F) to be recruited to join the Machine Learning
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. Connections working at New York University More Jobs from This Employer https://main.hercjobs.org/jobs/22186757/junior-research-scientist-in-the-division-of-engineering-x28-electrical-and-computer-engineering
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inference, longitudinal methods, survival analysis, regression modeling, machine learning, or prediction modeling are required, as well as experience with statistical software such as R, SAS, or STATA. Prior
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good command of English, both spoken and written; — experience in research on applied statistics and machine learning will be an additional advantage; — as teaching at the Faculty of Mathematics is
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Employer https://main.hercjobs.org/jobs/22174438/assistant-associate-full-project-scientist-machine-learning-data-analytics-advanced-bioimaging-center-department-of-molecular-and-cell-biology Return
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consideration will be made to candidates with experience in automation or machine learning. The postdoc will join a group which is focused on pioneering applications of modern machine learning methods, FAIR data
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brings complementary and/or additionally new expertise including AI/Machine Learning-based methodologies that can be developed for virtual ligand screening, reverse virtual screening (target fishing) and