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NYU Rory Meyers College of Nursing Path 1: Research Assistant: Laboratory for Computer-Human Intelligence in United States


The Laboratory for Computer-Human Intelligence in the Division of Engineering, New York University Abu Dhabi, seeks to recruit a motivated Research Assistant to work on cutting-edge machine learning / artificial intelligence / data science applications that utilize human signals (e.g. text, audio, physiology).

The Role

The Research Assistant will work on research projects in the Laboratory for Computer-Human Intelligence under the direction of the Principal Investigator Tuka Alhanai. Research projects range from implementing machine learning algorithms that measure cognitive outcomes, to visualizing patterns that map population-level health and well-being. The Research Assistant is expected to develop creative solutions to day-to-day technical challenges, think critically about meaningful next steps in the research process, and lucidly relay their thoughts, insights, and conclusions to high-level executive audiences and technical peers. It is not expected that the applicant be perfect at these tasks, but will motivated and self-driven to develop the necessary skills to master the role of a researcher.

Key Responsibilities:

In the capacity of a researcher, the individual is expected to generally conduct the following activities. The specifics are dependent on the nature of the project they work on.

  • Data Curation: Develop data ingestion engine(s) (appropriate for the data type) to organize the data that simplifies processing conducted with the data. Researcher will utilize any of sensors, front-end web-based applications, and databases to collect and organize data.

  • Multimodal Signal Processing: involves processing data of different types (e.g. audio, text, physiology, image, movement), using computational methods. Most data is noisy and needs to be cleaned and reduced into a salient representation.

  • Machine Learning: involves applying algorithms to automatically detect patterns in data and model outcomes of interest. Many if the latest modeling approaches are little understood, and require computational power to digest information beyond what humans are able to process.

  • Visualization: Representation of data and results in the form of plots, charts, and images. This helps convey to technical peers as well as the general public what contributions the work makes to knowledge. It is expected that this be rendered statically and/or dynamically in a web framework.

  • Documentation: involves structuring above work in a (a) software repository, (b) comprehensive comments in software, (c) development of a clear README, (d) journal/conference paper*, and (e) corresponding project website. This ensures work is reproducible and accessible to both technical peers and the general public.

*researcher should target top-100 publications here:

Technical Experience

The successful applicant will have the following technical experience in:

  • The development of end-to-end applications (e.g. databases, algorithms, visualizations).

  • Processing one or more data types/signals (e.g. text, audio, images, physiology).

  • Applying machine learning algorithms (e.g. regression, neural networks).

  • Utilizing the following programming languages/frameworks: bash, SQL, Python, HTML, Javascript, and Tensorflow/Pytorch, as well as source code version control (git).

  • Authoring peer-reviewed scientific papers.


The successful applicant should be self-driven and interested in the general domain of machine learning (e.g. latest ideas, research findings, research tools), contain a scientific curiosity for formalizing the underlying mechanisms of the observable world (e.g. do we make conclusions based on the words in speech, or intonation of speech?), and is passionate about creating timeless systems, with an attention to detail and zeal for quality.

Further Information:

For a sense of work performed in the lab, explore this portfolio:

If you have any questions, please email:

Professor Tuka Alhanai, Lab Principal Investigator at

The Division

Engineering research at NYU Abu Dhabi crosses the boundaries of traditional engineering disciplines and encompasses broad interdisciplinary areas that embody key characteristics of our age. In the face of global competition, dwindling natural resources, and the complexity of societal needs, the leaders of technological enterprises will be those who can innovate, are inventive and entrepreneurial, and understand how technology is integrated within society.


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.

UAE Nationals are encouraged to apply.