HCI Postdoc

Multiple postdoctoral positions are immediately available for HCI and applied ML/AI research that designs interventions and experiments to dynamically enhance and personalize real-world educational technologies, spanning K12, university courses, MOOCs, and learning by crowd workers. 

The postdoc will set the agenda for research questions in collaboration with Joseph Jay Williams and Min Yen Kan, who are particularly interested in creating systems that combine rigorous randomized experiments with crowdsourcing and human computation, applications of statistical machine learning (e.g. bandits & reinforcement learning, NLP, recommender systems), and theories from cognitive and social psychology (e.g. self-explanation, analogical comparison, growth mindset).

The postdoc will be based at the National University of Singapore's Institute for the Application of Learning Sciences and Educational Technology (ALSET) and the School of Computing, working with Joseph Jay Williams and Min Yen Kan. ALSET provides unique access to data about university students, and opportunities to create large-scale personalized interventions to help NUS's 30 000 undergraduate students as well as the Singaporean workforce's demand for continuing education. Based on the postdoc's interests, there will be opportunities to work with and visit close collaborators at Carnegie Mellon, and there could be similar options at other universities (like Harvard and KAIST). The appointment is for one year, with the possibility of renewal based on mutual interest.

The postdoc will play a key role in which projects are pursued, but illustrative examples of potential research directions are:
  • Developing new systems for crowdsourcing the design of online math problems and lessons, using multi-stage workflows that incorporate input from students, crowd workers, instructors, and learning scientists.
  • Creating and evaluating tools that enable collaboration between instructors and researchers, such as co-design of interventions and personalized lessons, and coordinated analysis of data about learning outcomes for students with different characteristics. 
  • Investigating why and when prompting students to explain text/video lectures promotes learning, and understanding the effect of multi-modal interfaces that incorporate writing, speaking, and video creation. Teaching metacognitive skills and self-regulated learning of study behaviors, taking a user-centered approach to designing social-psychological interventions for enhancing motivation such as Growth Mindset and Wise Feedback. 
  • Interpretable and Interactive Machine Learning Systems for dynamically enhancing and personalizing instruction, especially from the perspective of combining human computation with techniques from multi-armed bandits/reinforcement learning, Bayesian optimization, applications of deep learning to natural language processing. 

See www.josephjaywilliams.com/postdoc for project directions with a greater focus on psychology or education.

Application Instructions

To apply for the position, please email Joseph Jay Williams (williams@comp.nus.edu.sg) and Min Yen Kan (kanmy@comp.nus.edu.sg) with the subject line "Postdoc in Dynamically Enhancing & Personalizing Educational Technology" and your name, with the following as attachments: 

(1) Curriculum Vitae (Complete).  
(2) Names and contact information of 3 references who are familiar with your research. We will follow up with your references to secure their recommendation letters on your behalf.

In your email application, please include a brief explanation of your research interests and how they fit with this position (in lieu of a formal cover letter).  Applications will be accepted on a rolling basis until the position is filled, the first round of review will occur by August 28.