We are actively looking for highly motivated and talented ostdoc research fellows, PhD, Masters, Undergraduate students
to work in the areas of explainable AI, applications of deep learning, human-computer interaction, ubiquitous / pervasive computing, internet-of-things and sensors, data analytics and data visualization. If you are interested in working with us, please email your CV and transcript!

If you are interested in working with our lab as a postdoctoral fellow, we have open positions in the areas of explainable AI, healthcare and urban data analytics and visualization, or medical devices sensing and persuasive interfaces. We are seeking outstanding candidates holding (or soon to be holding) a PhD in Human-Computer Interaction, Computer Science, Electrical Engineering, or related field. Please enquire and send your CV, cover letter and a brief statement of research interests.

If you are a prospective PhD student, please check out details of the NUS Computer Science PhD programme and apply.

Here are some descriptions of possible projects and requirements.

Interactive Explainable AI – Postdoc, PhD Student

The prevalence and ubiquity of deep learning and AI in society is driving the need for their responsible use. To make AI more trustworthy, it needs to be explainable, privacy-preserving, and human-centered. While much recent research on Explainable AI (XAI) has provided many explanation techniques, they remain unusable for end users and domain experts. Therefore, this project aims to develop novel explainable AI algorithms and evaluation methods to improve the usability and usefulness of AI.

We are looking for talented candidates to join our multidisciplinary team. The project is investigating computer vision, artificial intelligence, data visualization and human-computer interaction to develop effective human-AI collaboration and explainable AI.

Expected Skills:

  • For PhD candidates: Masters or Bachelors in Computer Science, Electrical Engineering or related disciplines
  • For Postdoc candidates: PhD in Computer Science, Electrical Engineering or related disciplines with a background in human-computer interaction and cyber-physical systems
  • Expertise in computer vision, machine learning, human-computer interaction, machine learning, and/or data visualization is highly desirable
  • Competency in developing and implementing algorithms, and programming
  • Excellent writing and presentation skills
  • Ability to work independently (50%) and team projects (50%)

To apply, please send your research statement, CV and names of 3 referees (name, institution, email) to Dr. Brian LIM (brianlim@comp.nus.edu.sg). Only shortlisted candidates will be contacted.

Data Analytics, Cyber-Physical Systems and Human-Computer Interaction – PhD Student

We are looking for highly talented and motivated candidates to work on developing explainable machine learning models for analyzing electronic medical records and sensor-driven healthcare data. The project will leverage deep learning and other machine learning techniques to (1) support accurate logging of lifestyle behaviours, (2) recommend healthy behaviours and provide context-aware interventions, and (3) providing decision support to clinicians to improve disease diagnosis.

Preferred qualifications & requirements:

  • Masters or Bachelors in Computer Science, Electrical Engineering or related disciplines

  • Interest and experience in working with Internet-of-Things, wearable sensors, and mobile apps for healthcare applications
  • Competency in developing and implementing algorithms, and programming
  • Excellent writing and presentation skills
  • Ability to work independently (50%) and team projects (50%)

To apply, please send your research statement, CV and names of 3 referees (name, institution, email) to Dr. Brian LIM (brianlim@comp.nus.edu.sg). Only shortlisted candidates will be contacted.

Public Health Data Analytics – Intern

We are seeking data science interns to help analyze healthcare data. This project aims analyze a large dataset from mobile and wearable devices to understand human behavior. Undergraduate or graduate students with relevant background in Computer Science, Computer Engineering, Data Science, or related fields are invited to apply.

Requirements:

  • Scripting (R, Python, RESTful APIs)
  • Machine Learning (classifications, clustering, time series modeling, segmentation)
  • Familiar with tools for Statistics and Machine Learning (SPSS, SAS, JMP, R, Weka)
  • Familiar with relational databases (MySQL, PostgreSQL)

Desirable Experience

  • Familiar with tools for Geographic Information Systems (GIS): PostGIS, QGIS, GeoServer and OpenStreetMaps
  • Familiar with information visualization or interaction design. Capable of designing and implementing interfaces in Javascript, D3, Processing, etc

We are looking for one or multiple candidates who can fulfill all or part of the aforementioned requirements. Interested candidates should send your grade transcript and CV to Prof. Brian Lim (brianlim@comp.nus.edu.sg).

Data Visualization – Interns and Research Engineers

We are seeking web developer interns and research engineers to help build a web-based toolkit to visualise data in smart cities. Students or recent graduates with relevant background in Computer Science, Computer Engineering, Electrical Engineering, or related fields are invited to apply.

Singapore is becoming a smart nation with the increasing release of open data and the use of data analytics. However, this urban data needs to be used smartly to provide better services for citizens and government agencies. One way to do this is to provide good visualisations to help users better understand the data analytics, find patterns, and generate insights. Furthermore, urban data comes in many varieties and is applied to many application domains (transportation, air quality sensing, operations maintenance, etc.). Therefore, we are building the Urban Visual Analytics Toolkit to make it easy to build visualisations to satisfy this wide range of uses. Come help design and develop the features to make compelling and creative visualisations for the Smart Nation.

Requirements:

  • Working knowledge in HTML, CSS, Javascript and various web libraries such as jQuery, D3.js and THREE.js
  • Working knowledge of how to use REST APIs, AJAX methodology
  • Working knowledge of coding best practices
  • Experience/exposure to geospatial data and concepts and tools (e.g., PostGIS, QGIS, GeoServer OpenStreetMaps)
  • Experience/exposure to sensors and sensor data concepts
  • Experience/exposure to data visualisation
  • Possesses good design sense to build beautiful visualisations and user interfaces

Interested candidates should send a transcript and CV to Prof. Brian Lim (brianlim@comp.nus.edu.sg).