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architectures adapted for biomedical applications; and using Python, SQL, PySpark, AWS cloud computing environment, Databricks, Git-based workflows, R and SAS. Michigan Medicine conducts background screening and
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teaspoon languages, writing programs in the Snap! programming language (https://snap.berkeley.edu/ ), and learning to transfer their knowledge to industry standard notations like Python, Processing, and HTML
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. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem
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5, 2025, but the position is open until filled. Applications must be submitted online at https://workforum.memphis.edu/ and include a cover letter, CV, unofficial transcripts, two representative
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(e.g. fuel cells, batteries, heterogeneous catalysts, interfaces) Proficiency in high-level programming languages, e.g. Python Previous supervision of graduate students, as well as laboratory
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or several of the following areas: A solid foundation in programming and system development, particularly using Python and machine learning frameworks. Should be comfortable working with machine learning
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important - Prior experience with density functional theory or machine learning is desirable - Proficiency in the Python programming language is important, as well as Fortran - Strong written and oral
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 5 hours ago
YOU MUST APPLY TO THIS POSTING AT THIS APPLICATION SITE ONLY : https://www.utsc.utoronto.ca/webapps/cupehiring/dept/cms/app/sl If you have any issues applying, please contact Kelly Squier
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for QMSS (including which course(s), if applicable) and the skills (e.g., analytical tools such as Excel, R, Tableau, Python, etc.) and experiences (e.g., jobs, internships, research, coursework, teaching