ML NLP Post doc

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ML NLP Post doc

Tufts University
Country of Position: 
United States
Contact Name: 
Shuchin Aeron
Subject Area: 
Machine Learning for Signal Processing
Speech and Language Processing
Start Date: 
20 September 2022
Expiration Date: 
01 January 2023
Position Description: 

Tufts University has an opening for a post-doctoral researcher to engage in a cross-cutting project focusing on the development of and use of Natural Language Processing (NLP) for social sciences applications. Recent advances, starting with the now classical word2vec approach to models built using attention and transformer networks such as BERT and GTP3 have shown tremendous potential for natural language modeling and automated interpretation. While most applications currently focus on content generation, user interfaces (chatbots), and understanding news content, this project aims to use NLP as a major assistive technology to gain insights into student work and understanding in STEM education systems. This presents novel challenges, to interpret, for example, whether a student is arguing from intuition or from formal principles, whether they are excited or intimidated, whether they are uncertain or confident. The data may be written work or audio-video streams of  conversations, and analysis of the latter may involve video processing of  gestures and tone of voice. This multi-modal analysis is the next frontier in NLP and will require novel advances in both statistical machine learning and deep learning architectures. This position provides a unique opportunity to develop and collaborate with exclusive data sets, in research designed to influence classroom teaching and impact.

Applicants must have a PhD in electrical engineering, computer science, applied mathematics, statistics, or a similar field; a background of research in the learning sciences would be helpful but is not required The ideal candidates will have experience with and a publication record in one or more of the following areas: modern methods of statistical signal processing, machine learning, optimization, or data science with applications to NLP. Programming experience in Matlab or python is highly desired and preferred. 

The post-doc will be jointly supervised by a team of faculty in machine learning (Prof. Eric Miller, Prof. Shuchin Aeron) and by a team of faculty in the learning sciences (Prof. Julia Gouvea, Prof. David Hammer).

For more information about this position, please email Prof. Shuchin Aeron ( Prof. Eric Miller ( and Prof. Bree Aldridge  ( Interested candidates should provide Prof. Miller with a copy of their CV, list of references, cover letter, and copies of relevant articles, theses, technical reports etc.

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