About the Role
The Laboratory for Computer-Human Intelligence in the Division of Engineering seeks to recruit a motivated Research Assistant to work on cutting-edge machine learning, artificial intelligence, and data science applications that utilize human signals (e.g., text, audio, physiology). The Research Assistant will collaborate on research projects under the direction of the Principal Investigator, Tuka Alhanai. Projects will involve implementing machine learning algorithms for measuring cognitive outcomes and visualizing health and well-being patterns at a population level. The ideal candidate will develop creative solutions, think critically about the research process, and communicate insights effectively to both technical peers and high-level executive audiences. Applicants are expected to be self-driven and motivated to develop the necessary skills for success in the role.
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Key Responsibilities
As a researcher, activities will include but are not limited to:
- Data Curation: Develop data ingestion engines tailored for specific data types, utilizing sensors, web applications, and databases to organize data for processing.
- Multimodal Signal Processing: Process diverse data types (e.g., audio, text, physiology, image, movement) using computational methods, addressing noise and creating clean, salient representations.
- Machine Learning: Apply algorithms to detect patterns and model outcomes in data, utilizing advanced algorithmic approaches that require substantial computational power.
- Visualization: Create plots, charts, and images to represent findings effectively for technical peers and the general public, rendering visualizations through web frameworks.
- Documentation: Ensure work is reproducible and accessible by organizing projects in a software repository, providing comprehensive software comments, developing clear READMEs, and contributing to journal/conference papers and project websites.
- The researcher should aim for publication in reputable journals and conferences.
Technical Experience
The successful applicant will possess technical experience in:
- Development of end-to-end applications including databases, algorithms, and visualizations.
- Processing multiple data types/signals (e.g., text, audio, images, physiology).
- Applying machine learning algorithms (e.g., regression, neural networks).
- Utilizing programming languages/frameworks such as bash, SQL, Python, HTML, JavaScript, TensorFlow/PyTorch, and source code version control (git).
- Authoring peer-reviewed scientific papers.
Attitude
Candidates should be self-driven and enthusiastic about machine learning, maintaining scientific curiosity, and an eagerness to formalize the mechanisms of the observable world. The ideal applicant will show a passion for creating quality systems, with great attention to detail.
Further Information
For illustrative examples of lab work, a portfolio can be explored at: https://talhanai.xyz/projects.html
Educational Experience
A Bachelor’s degree (Master’s preferred) in Computer Science or a related field (Mathematics, Physics, Engineering, Economics, etc.) is required.
Contract Details
Applications will be considered on a rolling basis until the position is filled. Candidates who pass the review process may be accepted immediately. To be considered, all applicants must submit the following in PDF format:
- Cover letter
- Curriculum Vitae
- Transcript of degree
- Two letters of recommendation
Additional Program Information
UAE nationals are encouraged to apply. This position is part of the company's Kawader program, which supports outstanding graduates in gaining experience in a cutting-edge academic research environment. For further details regarding the program, requirements, and FAQs, please refer to the company's Kawader webpage: https://nyuad.nyu.edu/en/about/careers/postdoctoral-and-research/kawader-research-assistantship-program.html.
Equal Employment Opportunity Statement
The company 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 legally protected characteristics.
Sustainability Statement
The company aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at the company's sustainability webpage.
