Job Description

The Meta Reality Labs Research Team brings together a world-class team of researchers, developers, and engineers to create the future of virtual and augmented reality, which together will become as universal and essential as smartphones and personal computers are today. Just as personal computers have done over the past 45 years, AR, VR and MR will ultimately change everything about how we work, play, and connect. We are developing all the technologies needed to enable breakthrough AR glasses and VR headsets, including optics and displays, computer vision, audio, graphics, brain-computer interfaces, haptic interaction, eye/hand/face/body tracking, perception science, and true telepresence. Some of those will advance much faster than others, but they all need to happen to enable AR, VR and MR that are so compelling that they become an integral part of our lives.

In particular, the Meta Reality Labs Research Audio team is focused on two goals; creating virtual sounds that are perceptually indistinguishable from reality and redefining the human hearing.

These two initiatives will allow us to connect people by allowing them to feel together despite being physically apart and allow them to converse in even the most difficult listening environments. 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.

> Extremely low-power, energy-autonomous wearable design — sub-milliwatt and duty-cycled sensing architectures, analog/mixed-signal front ends, event-driven and always-on wake-up circuits, and self-powered operation via energy harvesting.

> Embedded real-time signal processing on resource-constrained hardware — ANC, echo cancellation, hear-through, adaptive filtering, and efficient implementations on MCUs and DSPs.

> Hearing biomechanics characterized through experimentation and numerical simulation.

> Conventional and ML-based signal processing — feature extraction, classification, regression and event detection, sequence/temporal modeling, self-supervised and transfer learning for scarce physiological labels, subject-independent generalization and calibration, sensor fusion across modalities, and on-device/TinyML inference (quantization, pruning, distillation) under tight compute and energy budgets.

This internship can be twelve (12) to twenty-four (24) weeks, with various start dates throughout the year.

Responsibilities

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 results

Qualifications

Currently 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-op