The Center for Interdisciplinary Data Science and Artificial Intelligence (CIDSAI) at NYU Abu Dhabi seeks to recruit a motivated and passionate post-doctoral associate to work under the supervision of Dr. Hanan Salam on the :

(1) Development of an Augmented Smart Classroom for Personalized Learning (SmartClass) serving as a test-bed for the collection and analysis of students and professors data, leveraging on data analytics and machine learning to improve learning outcomes and engagement in the classroom, and

(2) Development of personal GPT-powered AI tutors that use the knowledge from (1) to provide personalized recommendations and improve the overall learning experience for students. The project seeks to promote lifelong learning by revolutionizing traditional teaching methods and providing innovative tools for interactive and distance learning.

Key Responsibilities:

Research

• Conduct research and development on the Augmented Smart Classroom (SmartClass) platform, focusing on data collection, analytics, and real-time classroom monitoring.
• Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning.
• Develop and evaluate GPT-powered AI tutor systems, integrating insights from classroom data to deliver individualized learning experiences.
• Collaborate with interdisciplinary teams to create interactive, user-centered tools that support both in-person and remote education environments.
• Translate research findings into practical applications that support lifelong learning and pedagogical innovation.
• Contribute to scholarly publications, grant reports, and dissemination of research outcomes in academic and educational technology forums.
• Mentor undergraduate and graduate students involved in the research project, fostering a collaborative and productive research environment.
• Stay up to date with the latest advances in AI in education, human-AI interaction, and personalized learning technologies.

Minimum Qualifications

• Currently has or is in the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree from a recognized institution (no more than 5 years since completing the doctoral degree);
• Relevant research experience in at least one of the following: Social Robotics, human-robot interaction, human-computer interaction, Machine Learning, Affective Computing, Social Signal Processing, Computer Vision and speech processing, multimodal signals processing and fusion;
• Proficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow) with several years of practice;
• First-author peer-reviewed published papers (or under review);
• Excellent communication skills in English (oral and written communication)
• Willingness and capacity to work in a multidisciplinary environment consisting of PhD-level scientists, graduate students and undergraduate students
• Self-motivated with an ability to work independently and in a team to get the work done.
• Willingness to learn and confront new challenges.

Applications will be accepted on a rolling basis and candidates will be considered until the position is filled. For consideration, applicants need to submit in PDF format:

• Cover letter;
• Curriculum Vitae with full publication list;
• Research statement highlighting past and current research experience (1 page);
• Research project (1 page) explaining how the candidate sees their research fit in the research axes of the lab. Note, Dr. Hanan does not supervise research outside of the scope of the lab research axes;
• At least two letters of reference.

The appointment will be for two years, with the option to renew further depending on performance (in total not to exceed 5 years).

More information about professor Hanan’s lab can be found here: https://wp.nyu.edu/smartlab/

If you have any questions, please email Prof. Hanan Salam at hanan.salam@nyu.edu .

The terms of employment are very competitive and the position provides salary higher than internationally competitive rates for Post-Doctoral positions, in addition to substantial benefits (generous housing, transportation and travel allowances, educational subsidies for children), together with full health insurance and retirement contributions. The UAE does not levy income tax.

About NYUAD:

NYU Abu Dhabi is a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in their pursuit of academic and scholarly activity. This global university represents a transformative shift in higher education, one in which the intellectual and creative endeavors of academia are shaped and examined through an international and multicultural perspective. As a major intellectual hub at the crossroads of the Arab world, NYUAD serves as a center for scholarly thought, advanced research, knowledge creation, and sharing, through its academic, research, and creative activities.

EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity Employer

UAE Nationals are encouraged to apply.

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NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.

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