Gain access to top talents from reputable universities globally to work on your Deep Tech projects with co-funding of up to SGD$3,000/month from SGInnovate. These highly-skilled talents will bring in fresh perspectives that add value to your organisation. Increase your brand awareness by being a part of the programme’s outreach activities.
Head of Delivery (Singapore), Taiger
Data Platform Lead, ViSenze
Access to Top Talent
Attract top Deep Tech talents – undergrads and PhDs from reputable universities across the globe.
Attract top talent with an award of up to SGD$3,000/month from SGInnovate, in addition to the stipend provided by your organisation.
Increase your brand awareness by being a part of the programme’s outreach activities.
Bring in energetic students with fresh perspectives to test out new ideas or roles for your organisation.
Get plugged into the Deep Tech ecosystem through exclusive invites to various industry and community events.
Your organisation should be a startup specialising in Deep Tech with proof of financial stability.
Deep Tech Projects
Projects offered must be related to Deep Tech, such as Artificial Intelligence, Blockchain, Cybersecurity, Quantum, and Robotics
Mentors should demonstrate technical expertise, ideally with five years of technical and two years of mentorship experience.
SMART Optical Character Recognition
This is an image processing and data extraction system development. This system will be deployed and used by the banks and insurance companies to extract the data from the scanned copy of any supporting document for their further internal processing. The quality of the document images (bank statements, invoices/receipts, etc.) such as the resolution, brightness, and contrast might not be as good as we expect it to be for the system to be able to process it. We need to process the image to improve the quality to make it processable by the OCR and extract the necessary data from it. These are the three major processes in this project:
Social Media Inference Through Deep Learning
At Affable, we profile millions of users every day and use Machine Learning to infer things like: what are their interests? How old are they? Where are they located? We use a host of signals to make such inferences, including but not limited to their profile pictures, instagram posts and stories, and captions.
This project involves conceptualising, training and deploying Machine Learning models that can infer even more characteristics about social media users. Some of the characteristics we want to extract are psychographics, education level, job function, and income level.
The main challenges of this project are two-fold: volume and speed. Affable tracks over 1.5 billion social media posts and 300 million social media users. Machine Learning at this scale is challenging, time-consuming, but also very rewarding. You will get a first-hand experience in building models that are not only accurate, but also fast and are production-grade (some of our models run inference on over 20 million images per day).
Insurance Machine Learning by Google AI
Through technology and seamless integration, Axinan creates high-frequency products with a low premium due to accurate risk assessment based on our real-time risk engine. When dealing with fast-changing market condition and scenarios, it is important to be able to quickly create tailor-made products that can handle complex risk and fraud conditions.
Our technology is selected by Google for the latest cohort of startups for its Launchpad Studio program. With Google technologies and support from Google AI experts, we develop insurance products driven by AI and Machine Learning technology.
In this project, you will be working with the engineers and data scientists to develop cutting-edge Machine Learning models, improve accuracy and implement models in real-life insurance products. This includes models that analyse millions of features and models that run locally on mobile phones.
Extraction of Textual Streaming Data
Streaming textual data coming from online applications like chatbots, question forms and emails has its specifications in comparison with structured or semi-structured documented text. As usual, the text is written in free format, with missed punctuations, broken structures and spelling mistakes. The goal of this project is to extract all personal information from free text.
Deep Learning on Echocardiograms
We are building a global data network housed in some of the world's pre-eminent imaging labs and academic institutions. This data serves as the foundation for Machine Learning and statistical analysis for disease prediction studies. We are collaborating with some of the world’s top cardiovascular researchers to structure, analyse and publish the data, while incorporating the algorithms into a SaaS based product for clinical uses. You will be required to support and participate in Machine Learning trials, organising and analysing large volumes of echocardiograms. There will be opportunities to gain experience with a variety of Deep Learning classification and segmentation techniques in collaboration with some of the world's premier cardiology centres.
Information Extraction In the Legal Domain
At INTELLLEX, we handle millions of legal documents and we want to build an automated end-to-end system to extract useful information from the legal documents. For each document, we need to identify the areas of law being discussed and legal keywords being used.
In this project, you will be involved in the development of an automated end-to-end system - from data exploration, pre-processing, training and tuning Machine Learning classifiers, and running Machine Learning experiments to evaluate the performance of the system against standard benchmarks.
Forecasting of Financial Data Using Machine Learning
In this project, you will build a fast and reliable time series forecasting pipeline for sales data. This project will allow you to work on a big financial dataset, and evaluate internal and external factors affecting sales. This project will require you to assess various forecasting engines to identify the right model based on the data for the customer. The main aim of the product will be to provide our customer with the most accurate forecast with actionable insights.
Information Extraction Using Natural Language Processing
In this project, you will be developing an automated system which requires zero configuration or upfront annotations, using the latest developments in the fields of Computer Vision and Natural Language Processing for information extraction. You will work on the large dataset collected from the customer. The primary objective of this project is to automate the task of information extraction from data and process it in such a way that it can be utilised in our product.
Semantic Generative Compositions in Advertising
Pencil uses generative and reinforcement techniques to give machines a practical and usable understanding of what creativity is in the context of advertising - potentially the world's largest creative industry. In this project, you will be involved in specific challenges related to shipping a viable system for semantic generative compositions in the advertising space. Your goal will be delivering a working prototype with test users by the end of the project.
Predictive Analytics In Maritime
90% of the world trade travels via maritime, at least once in its lifetime. Portcast wants to apply Machine Learning to the extensive datasets from the maritime industry that it captures, and convert it into actionable insights. The project scope is to transform the raw datasets (from econimic indices, geo-spatial data, to news/sentiment information) into insights and patterns that would be interesting not just for the logistics industry, but to the finance and insurance companies as well.
Analysis of Human Biopsy Samples with Computer Vision
Cancer is one of the leading causes of death in the world and affects patients and their families for extended periods of time. Although there has been a significant amount of progress in treatment options, early diagnosis is still the main factor in determining the patient's prognosis. Qritive's mission is to enable doctors to diagnose cancers faster and more accurately, and consequently improving the patient's chances in fighting these diseases. To achieve this goal, Qritive is leading several joint projects to build these systems. The project collaborators are the two most prominent hospitals in Singapore, with a panel of expert clinical researchers and clinicians involved in these projects. The project is based on recent advances in Deep Learning and Computer Vision technologies. The goal is to reduce the time spent by doctors on the analysis of cancer tissue images and reduce the number of misdiagnoses.
Image Pre-Processing Through Deep Learning
Image pre-processing is a vital step to create segmented data of images for downstream processing. You will be involved in creating a state-of-the-art image processing framework by using Deep Learning methodologies such as Convolutional Neural Networks (CNNs) and bi-directional long/short-term memory units.
Contextual Data Extraction
Identifying and extracting the original context of the document is a significant step in automatic information extractions tasks. In this project, you will be extracting relationships between texts which are contextually related. This makes it easy to import the extracted data into a database or to provide it as a variable into an application.
Build Smart Contracts on the Ethereum Blockchain
In this project, you will design and implement smart contracts on the Ethereum Blockchain for the crypto art marketplace, crowdfunding and other related products. You will manage their deployment and maintain them over the product lifecycle. At the end of the apprenticeship, the candidate will learn how to write Ethereum smart contracts and how to build consumer-facing web applications based on them.
Design Asset Tracking on Blockchain
We are designing a system for providing tracking, verification of possession and counterfeit prevention of limited-edition, high-value physical goods on the Blockchain without any centralised trusted authority. BlockPunk uses several cutting-edge developments in Cryptography, specifically zero-knowledge proofs that enable a prover to demonstrate to an untrusted verifier knowledge of a secret without revealing any information about the secret itself. You will need to be familiar with recent advances in succinct and non-interactive zero-knowledge proofs (such as zk-SNARKs, Bulletproofs & zk-STARKs) and be capable of implementing them in both hardware and software.
Implementation of Blockchain Data Structure
The purpose of the project is to build a provably fast, scalable, secure, and permissionless Blockchain. The project will be primarily implemented in Go, and the core products will be open-sourced. Significant open-source contribution experience will be considered very favourably. FissionWorks is supportive of our engineers and researchers being active and speaking in their technical and research communities globally.
Development of Blockchain Infrastructure for Digital Assets
The project will focus on the building out of an electronic marketplace hub facilitating over-the-counter trades of digital assets, with the clearing and settlement of transactions done via the use of smart contracts.
Detecting Anti-Money Laundering Risk On Blockchain
Merkle Science detects AML risks on the Blockchain. In this project, you will be involved in a technically complex process which requires a combination of Blockchain and Machine Learning knowledge to come up with a risk score for each Blockchain wallet, taking into account over 100 parameters such as ransomware, time of transactions, no. of transactions, and days since existence.
Cybersecurity in IoT Edge Security
You will get to work on the state-of-the-art APIs for IoT dashboards; perform analytics and provide Cybersecurity to IoT networks; develop security protocols (SSL) on lightweight network routers/devices; design and develop different security protocols; along with cryptanalysis of various architecture and security protocols for embedded systems. You will also get to work on a broad domain of technologies, providing you with insights on various industry trends.
Structural Health Analytics
Structural Health Monitoring (SHM) refers to the process of systematically analysing the data from existing infrastructures like skyscrapers and bridges and extracting useful information about how they age. Such information enables predictive maintenance of critical infrastructures. In this project, you should take the initiative to see the product through the entire lifecycle, from proof-of-concept, to design and finally production.
Artificial Intelligence for High-Tech Manufacturer
In this project, you will be working hand-in-hand with FireVisor’s CTO and your mission is to build and grow the data platform that manufacturers of the future are going to use. We help high-tech producers, from photovoltaic to semiconductors, to make a change in this world by making technology like solar energy available to everyone. You will be involved in building AI models to detect defect anomalies and save millions of products. Join our team early on and craft the tech stack that will power future factories. You will have the opportunity to wear many hats and gain hands-on experience in many functions of the business. At the end of the apprenticeship, you will gain domain knowledge and become proficient in an industry that has not been explored much by other data scientists.
Wireless Power Transfer
In this project, you will be contributing to a new radio-frequency based far-field wireless power transfer platform. TransferFi is seeking for a self-motivated Embedded Design Engineer who has a strong technical background on the system-level embedded design from hardware to the firmware.
Radio Frequency Development
In this project, you will work with Software Defined Radios (SDR) comparing various signal modulations for performance analysis. You will also analyse multiple antenna designs. Transferfi is seeking for self-motivated Radio Frequency Engineers, who have strong technical backgrounds on system-level electromagnetics, signal integrity, power integrity design, analysis and antenna design. You will be contributing to a new RF-based far-field Wireless Power Transfer platform.
Designing Microwave-based Beamforming Radar Sensor
In this project, you will work with WaveScan's scientists in researching and developing our beamforming radar sensors. You will learn the entire R&D process of building radar-based sensor systems for specific applications, as well as understand the benchmark for the market development process necessary for corporate R&D jobs.
Laser Control and Radio-Frequency Design
The current ongoing project is building a portable single-axis atom interferometer which can measure gravity very precisely and help in accurately pinpointing hydrocarbon and mineral reserves, helping ease the energy needs of the world. You will be working closely with the product development team, an interdisciplinary mix with prior experience in Atomic Physics, biomimetic underwater robots, high altitude pseudo satellites and balloon satellites, and advised by leaders in Cold Atom Physics and navigation systems.
Atom Interferometry for Gravity Measurements
This project is building a portable single-axis atom interferometer which can measure gravity very precisely and help in accurately pinpointing hydrocarbon and mineral reserves, helping ease the energy needs of the world. You will be working closely with the product development team, an interdisciplinary mix with prior experience in Atomic Physics, biomimetic underwater robots, high altitude pseudo satellites and balloon satellites, and advised by leaders in Cold Atom Physics and navigation systems.
Quantum Machine Learning on Near-Term Quantum Computers
We are seeking two Quantum Machine Learning scientists to join our technical team in Singapore and contribute to the technical development of algorithms and applications for a proprietary Quantum Machine Learning suite. The goal is to implement variational Quantum algorithms using supervised and unsupervised Machine Learning methods and benchmark their performances against existing classical algorithms. These methods are executed on Quantum hardware (Rigetti’s and IBM’s), aided by classical subroutines on HPC and distributed environments.
Smart Robotic Biopsy Needle Path Planning
For the project, NDR aims to increase biopsy safety and accuracy using AI to plan the needle insertion location and angles. You will be developing 3D modelling software; image processing software for medical devices; conceptual and detailed software design for machines; motion control; I/O interfaces; as well as perform software installation, testing and debugging. There is a real hospital application with a clinician, and you will get the opportunity to work with experienced software engineers and AI experts.
Autonomous Driving in an Airport
RDR has a few autonomous driving related projects in Changi Airport, overseas airports and overseas seaports. There are many improvements that could be made to the robots navigating these environments. In particular, SLAM-based navigation, road-marking, object/obstacle detection and tracking of point cloud through clustering. These could be solved through Machine Learning, Deep Learning or other low-computing-cost techniques.
Intelligent Drone Security and Surveillance
The Drone Operations Center (DOC) is a command centre where UA pilots will be flying drones BVLOS. Connected to the UA via reliable and secure 4G/LTE links, the DOC makes command and control decisions when operating a fleet of drones across the country for a variety of use cases, such as surveillance, cargo delivery, or air taxis. In this project, you will be adding several Artificial Intelligence based capabilities to the DOC to increase the capacity of the drone in detecting people fighting, drunk people, and other public nuisances.
Please fill in your details below to find out more about the organisations and their projects. You would need to disable your pop-up blocker, if any, in order to download the PDF.
Open for Project
Open for Apprentices
Start of the Summation