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experience in relevant area. Knowledge or interest in Natural Language Processing, ideally as applied to big biomedical data. Programming using one or more of the following: Python, R, Javascript. Clinical
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and oral communication skills Ability to mentor and collaborate with graduate students What You Need to Do: Select the Apply button to begin your application! Submitting a cover letter and resume is
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Research Associate/Post-Doctoral Fellow - Institute for Research on the African Diaspora in the Amer
point for advanced teaching and research at the City University of New York (CUNY), the nation's largest urban public university. With over 35 doctoral and master's programs of the highest caliber
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, and Abilities Proficiency in programming languages commonly used in data analysis and machine learning, such as Python, R, or MATLAB. Must have effective oral and written communication skills; and
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English language and writing skills. Some experience in cryo-EM or eukaryotic protein expression is a plus. The successful candidate will join a highly collaborative group with extensive expertise in challenging
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should have: Demonstrated experience with computational fluid dynamics (CFD) is required. Experience with computer aided design (CAD) tools would be an asset. Experience with programming and scripting
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. The ability to read German, French and Italian. Please submit up to two publications for assessment. Note that only publications that are actually submitted with the application will be assessed; a list
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one of the following programming languages: R, Perl, Python, C/C++, JAVA, etc. Experience in cancer research and/or molecular biology will be an advantage. Preference will be given to those with
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applications (e.g. natural language processing, multivariate time-series data), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a
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of whole genomic data already available; and ii) investigating rates of evolution across the genome and their correlation with phenotypic traits across various subdivisions of the squamate body plan