Design and prototype novel wearable form factors and sensing hardware - electrode/transducer placement, mechanical and electrical integration, and ultra-low-power or self-powered architectures - for on-body biosignal acquisition Build and run wearable data capture setups: instrument prototypes, define and execute data collection protocols with human participants, and assess signal quality, repeatability, and artifact robustness across sessions and users Design and implement novel algorithms to collect and process, in real time, data from different sensors Deliver proof-of-concept demonstrations of the developed technologies to a team of researchers and other XFN partners Work closely with researchers on innovative project proposals, timelines, and milestones Communicate research plans, progress, and resultsCurrently has, or is in the process of obtaining a PhD degree in the field of Acoustics, Computer Science, Mechanical Engineering, Electrical Engineering or related STEM fields 2+ years experience with independent research as evidenced by publications and/or conference presentations 2+ years experience with computer aided design, acoustic simulation tools or programming languages such as MATLAB or Python Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment Intent to return to full-time degree program after completion of the internship Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading journals or conferences Experience working and communicating cross functionally in a team environment Intent to return to degree-program after the completion of the internship/co-opMeta builds technologies that help people connect, find communities, and grow businesses. The Devices and Hardware Research team of the Reality Labs Research Audio is looking for innovative PhD student interns interested in one or more of the following areas: >Electrophysiological and bio-signal sensing technologies and the associated signal processing - EEG, EMG, EOG, ECG, PPG, EDA, and other wearable biopotential/physiological modalities, including electrode and front-end design, artifact rejection, and robust on-body signal quality.