Description:
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: http://www.guide2research.com/topconf/
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.