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.
RMIT Work Experience in Biotechnology - start Feb 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 November.
Work Experience in Biotechnology
BIOL1302
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
Work Integrated Learning in Data Analytics
MATH2191
This work integrated learning course addresses the application of analytics and statistics in a real world situation for final year Master of Analytics, Master of Statistics and Operations Research and Bachelor of Analytics students. The projects include data pre-processing and cleaning, data wrangling and exploration, data visualisation (such as dashboard), time series analysis, multivariate analysis, predictive modelling, quality control, regression, machine learning, , experimental design and optimisation. Computation tools include in particular querying language (SQL), R, Python, SAS, and Matlab. Our WIL projects have helped big and small companies improving their service and efficiency using current analytics and data science techniques. The WIL also provides a pathway for industry to recruit excellent graduates. Some employers report that our students bring fresh ideas and approaches to the workplace, sharing the latest research and thinking in the field they study.
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).
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).
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.