Please apply at this link: http://forms.ri.edu.sg/RSIapps2018
|Deadline for applications is 21st February (Wed) 4:00pm. If you submit more than one application, only the latest submission will be considered.
Do note that you are also allowed to take RSI projects under the SRP programme. Only shortlisted candidates will be notified via email for an interview.
Pls email Dr Abigayle Ng at Abigayle.Ng at ri.edu.sg for any clarifications.
Title: Coral Feeding
Synopsis: Hermatypic “reef-building” corals are polytrophic: while mainly autotrophic (i.e. obtaining energy through photosynthesis by their symbiotic algae), they also acquire energy through heterotrophy (i.e. feeding on plankton and organic particulate). It has been suggested that corals’ abilities to feed on, and benefit from, particles in suspension or trapped in sediment is a major strategy allowing corals to persist in highly turbid reef environments, such as those found in Singapore. Corals have also been shown to ingest harmful inorganic particulates such as microplastics. This project will investigate 1) what some corals on Singapore reefs feed on in the field, and 2) controlled aquaria experiments to determine the feeding and prey capture abilities of corals (i.e. size and amounts of prey).
Looking for 2-3 students.
Principal Investigator: Dr Abigayle Ng (RSI); Dr Jani Tanzil (SJINML)
Pre-requisites: a) Independent and committed to the project; b) Interest in biology and conservation; c) able to commit to doing labwork during school term (after classes) and school holidays (at least 2 weeks)
Remarks: Project will involve upkeeping a live coral tank in school and lots of microscopy work
Contact: abigayle.ng at
Title: Activated carbon as rain garden supplements
Synopsis: Urbanization coupled with deforestation has resulted in major disruption of the microclimate as well as global climate. One aspect of the climate change is an upsetting of the hydrologic cycle leading to droughts and sudden storms. Pollution from industrialization and the urban way of life add to the problem as toxic contaminants such as heavy metals are washed into water ways regularly and particularly so during storms. This has spurred governments to put more effort into developing storm water management solutions. Rain gardens with its good water holding capacity and ability to sequester heavy metals from water bodies via adsorption by filter media poses as a very likely solution. Activated carbon (AC) that is already widely used to purify liquids and gases in a variety of applications is an attractive material to use in the filter layer of rain gardens. High costs however has restricts its applications. Moreover, commercial ACs are produced from coal, which is a non-renewable resource and coal mining also has devastating effects on the environment. This project explores the use of alternative natural materials in the production of low-cost AC that can be applied to rain gardens.
Looking for 4 – 6 students (2 groups)
Principal Investigator: Dr Lee Zhiying (RSI), Dr Grace Lim (RSI)
Pre-requisites: a) Dedicated and committed to research work; b) able to commit to long hours of lab work during holidays; c) enthusiastic students with an interest in environmental science
Title: Designing filter materials for improving water quality in LIDs
Synopsis: Low impact developments such as green roofs and rain gardens have great potential and application not only in reducing urban heat islands, enhancing biodiversity and aesthetic appeal but also water treatment and stormwater management. This project aims to design and evaluate environmentally sustainable substrates to support LID infrastructure to improve the water quality and optimise efficiency of such systems for urban water management.
Looking for 2-3 students
Principal Investigators: Dr Grace Lim (RSI) & Dr Abigayle Ng (RSI)
Pre-requisites: a) Independent and committed to the project; b) strong interest in environmental sciences; c) creative and able to innovate.
Title: Unravelling machine learning and artificial intelligence (AI) on disruptive technologies.
Synopsis: Smart disruptive technologies such as gesture recognition in 3D space require increasingly complex hardware such as micro radars and adaptive algorithm to handle them. See Google project Soli for a better idea. This project works on collision avoidance driving systems that can be implemented in autonomous and semi-autonomous systems by looking at vision-based or radar-based systems using Machine Learning and Artificial Intelligence techniques.
Looking for 3 students.
Principal Investigator: Dr Tan Guoxian (RSI)
Pre-requisites: Any basic programming experience, or willing to learn. Basic understanding in machine learning or data analytics a plus, but not a pre-requisite
Title: 3D printed prosthetic hand
Synopsis: This project is an engineering project with an internship and experiential research program at TTSH to develop and test a 3D printed prosthetic hand with TTSH patients, under the advice and guidance of RSI scientist, TTSH medical doctor and TTSH prosthetic engineers. Students will benefit from an intensive medical apprenticeship at TTSH to look into both the medical and engineering aspects of rehabilitative technology.
Looking for 2-3 students.
Principal Investigator: Dr Tan Guoxian (RSI) and Tan Tock Seng Hospital (TTSH)
Title: Automatic Speaker and Speech Recognition
Synopsis: Amazon Alexa, Amazon Echo, Google Home, Microsoft Cortana and Apple Siri. What do all of them have in common?
For one, they may face some difficulties when handling locally-accented English and context. A national speech project as part of the Smart Nation initiative involving sensors and emerging technology is underway to come up with innovative applications that are catered to the local context and accent. This project looks at advances in deep learning and artificial intelligence techniques to innovate in the speech recognition domain.
Looking for 3 students.
Principal Investigator: Dr Tan Guoxian (RSI), IMDA Data Analytics Research Team
Pre-requisites: Any basic programming experience, or willing to learn. Basic understanding in machine learning or data analytics a plus, but not a pre-requisite.