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Bioinformatics/Genomics and Cancer Biology is desirable. Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab
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required) skills: experience in any of the following areas is especially valued: synaptic plasticity, Python programming, structural biology, AI / machine learning, calcium imaging, FRET sensors
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, you will be responsible for working to solve healthcare challenges through an evidence based approach. These solutions will be found through machine learning and building applications within a scripting
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, you will be responsible for working to solve healthcare challenges through an evidence based approach. These solutions will be found through machine learning and building applications within a scripting
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peer-reviewed publications and/or software packages. Knowledge about statistics and machine learning algorithms. Strong programming skills (R and Python/Perl/Java) Programming in UNIX/LINUX environment
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variant GWAS/ExWAS. We are also developing novel machine learning methods to improve risk gene prediction and variant interpretation. This role will focus on the analysis of large-scale human genetics
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. Strong background in laboratory medicine and test utilization highly desirable. Familiarity with artificial intelligence and machine learning concepts. Excellent communication skills, both written and
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, Bioinformatics, or a related field (e.g. statistics, computer science, or quantitative biology) Experience in the application and development of computational methods/tools or machine learning algorithms Good
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collaborative team. Strong communication skills, both written and verbal, with the ability to convey complex scientific ideas to a diverse audience. Experience with machine learning and/or statistical modeling
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, Bioinformatics, or a related field (e.g. statistics, computer science, or quantitative biology) Experience in the application and development of computational methods/tools or machine learning algorithms Good