Principal Researcher, Multimodal Neural Models

Build multimodal neural representations

Study models that connect neural activity, muscle signals, task context, and behavioral feedback. Your work will shape WABO’s research baselines and evaluation practice.

What you will own

• Study multimodal neural representations across task conditions and behavioral outcomes.
• Establish rigorous data alignment, validation, and benchmarking practice.
• Improve evidence for robustness, interpretability, uncertainty, and task-conditioned performance.
• Build reusable research foundations for responsible evaluation.

What we value

• A PhD, or exceptional research depth, in artificial intelligence, computer science, biomedical engineering, computational neuroscience, electronic information, or a related field.
• Strong PyTorch experience and a deep understanding of temporal modeling, representation learning, or multimodal learning.
• Expertise in modern machine learning, representation learning, or multimodal research.
• The ability to design models, optimize training, run disciplined ablations, and communicate publication-quality results.
• Careful experimental judgment around leakage, evaluation bias, and statistical robustness.

Additional strengths

• Representative publications in machine learning, language, neural engineering, or biomedical signal processing.
• Experience with EEG, EMG, ECG, eye tracking, wearables, or other physiological time-series data.
• Experience with rigorous evaluation, uncertainty estimation, or deployment research.

What WABO offers

• Ownership of a central research direction within WABO’s neural intent program.
• Access to task-conditioned, multimodal research data under appropriate authorization and governance.
• Support for publications, patents, academic exchange, project incentives, and long-term growth.

Apply

Send a concise introduction, selected publications or systems work, and the research question you want to test with WABO.