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Melbourne, Victoria, Australia
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- Data visualization Data analysis Data modelling Risk, audit and compliance Security (cybersecurity and IT security)
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Work Integrated Learning in Applied Mathematics and Statistics
MATH2197
TO EDIT The project addresses the application of analytics and statistics in a real world situation and is a capstone project for final year Master students. Our students have extensive knowledge in data extraction and preprocessing, data wrangling and exploration, data visualization, machine learning, forecasting, multivariate analysis, quality control and experimental design. Computing skills include querying language (SQL), scripting language (R, Python) & statistical language (R, SAS).
RMIT Work Experience in Biotechnology - start July 2024
The intent of work placement is for participants to gain work experience at a level commensurate with Master in Biotechnology . A student could work individually or in teams undertaking biochemistry, molecular biology, microbiology, genomics, bioinformatics or related biotechnology projects. Student(s) could either assist in developing new assays or testing more samples with an existing assay. All placements need to be submitted through our internal form: https://app.smartsheet.com/b/form/edbfbb5b2d5941719d497fe9aa83c75f Our students prefer in-person experience. If you would like to offer an in-person experience, please submit your request latest by 15 March.
Industrial Applications of Mathematics and Statistics - Team projects
MATH2197
This course is for undergraduate students in Applied Mathematics and Statistics. Students will work in group on a problem proposed by the company. Their main technical skills are in data analysis, data visualisation, optimisation, quantitative methods and computer programming but their strong analytical and problem solving skills are useful for a large range of projects.
Work-Integrated Learning in Data Analytics - Team project
MATH2191
The project addresses the application of analytics and statistics in a real world situation and is a capstone project for final year Master students. Our students have extensive knowledge in data extraction and preprocessing, data wrangling and exploration, data visualization, machine learning, forecasting, multivariate analysis, quality control and experimental design. Computing skills include querying language (SQL), scripting language (R, Python) & statistical language (R, SAS).