Research Assistant

Stevens Institute of Technology•Hoboken, NJ

About The Position

The Movement Control Rehabilitation (MOCORE) Lab seeks a part-time XR Research Assistant to support the development of extended reality (XR) applications for motor rehabilitation research. The primary focus of the role is developing the software foundation for an AI-driven adaptive training control system — building the pipeline that links offline performance analysis to automated, real-time adjustment of experimental task parameters. Supporting responsibilities include extending the lab's existing virtual reality (VR) paradigms into augmented reality (AR) and prototyping real-time interaction and visualization features on standalone XR hardware. The position suits a recent graduate with strong Unity development skills, a working knowledge of applied AI/ML, and the ability to rapidly assess feasibility and prototype across both AR and VR. Beyond hands-on development, the assistant will serve as a technical resource to the research team — scoping approaches, estimating effort, and recommending implementation pathways.

Requirements

Master's degree in Computer Science or a closely related field.
Demonstrated expertise in artificial intelligence and machine learning systems.
Demonstrated ability to prototype applications in extended reality (both AR and VR).
Proficiency with Unity for XR development.

Nice To Haves

Experience developing for standalone VR/AR headsets (e.g., Meta Quest) and porting applications across XR platforms.
Experience with real-time hand tracking, hand kinematics, shaders, or particle systems.
Familiarity with hardware–software integration and data pipeline development.
Exposure to integrating offline analysis (e.g., MATLAB) into interactive/closed-loop systems.
Interest in motor rehabilitation, biomedical, or healthcare-related applications.

Responsibilities

Develop the software pipeline for an AI-driven, closed-loop adaptive training control system — including scaffolding to ingest offline analysis outputs and automatically adjust task parameters (e.g., difficulty, visual feedback) on a trial-to-trial basis.
Assess technical feasibility of the adaptive control approach, estimate development effort, identify obstacles, and recommend implementation pathways to the research team.
Convert existing immersive VR rehabilitation tasks into AR counterparts, including spatial registration of virtual elements (e.g., targets, controlled objects, motion trajectories) to real-world surfaces.
Establish and validate the hardware–software connection between experimental devices and standalone XR headsets (e.g., Meta Quest).
Implement real-time hand tracking, overlay, and visual-feedback features (e.g., accuracy-driven color modulation), with attention to rendering latency and user experience.
Build data capture and replay functionality, including saving hand kinematic data and re-projecting recorded sessions as playback.
Document technical progress and coordinate with lab personnel to align development with research objectives.