Research Fellow / Engineer, Chemical Plume Tomographic Algorithm
As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team to develop a 3D chemical plume tomographic algorithm using machine learning techniques and CFD data.
- Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.
- Meeting the project deliverables within the project timeframe, which consists of the following responsibilities:
o Performing computational fluid dynamics (CFD) runs to continually update and collect data based on project requirement.
o Perform data cleansing, preparation, visualization and analysis on the dataset collected
o Research on and implement the state-of-the-art predictive algorithms technique that can predict concentration patterns based on source release points and wind conditions
o Perform algorithm testing and evaluation
o Work closely with our collaborator to collate feedback for algorithm design
- Assists in co-supervision of Final Year Projects (FYP) or capstone projects students together with the project PI
- Assists PI in drafting of reports, conference proceedings and journal articles based on the outcome of the projects
- Prepares and shares fortnightly report of results from project work with PI
- Support and coordinate procurement and maintenance of the software/hardware under the charge of the PI
- Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
- Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.
- Have relevant competence in the areas of data analytics, machine learning, python programming and are familiar with data analytics software and platforms such as JupyterLab, SciPy ecosystem, scikit-learn libraries, tensorflow libraries.
- Knowledge in Computational Fluid Dynamics, ability to use OpenFOAM is a bonus
- A Bachelor, Masters or PhD in Data Science or Engineering
- Fluent verbal and written communications.
Applications close: 30 Jun 2023 Singapore Standard Time