Wavelet Analysis Summer Research Intern
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Job Description
About the Company:
This is a mission-driven startup focused on the intersection of clinical sensor technology, advanced signal analytics, and AI. They are developing innovative solutions by extracting meaningful patterns from noisy data to improve healthcare and other applications.
Job Description:
Wavelet Analysis Summer Research Intern
This summer research internship offers the opportunity to work on developing innovative wavelet-based denoising techniques to enhance correlation across multi-sensor systems. The intern will be responsible for developing algorithms that extract meaningful patterns from noisy data. This position can be located in Palo Alto, CA (Hybrid or Remote Available). The duration is 8-12 weeks during Summer 2025.
What You’ll Do:
• Implement and optimize wavelet denoising pipelines using Python, R, MATLAB, or similar tools.
• Evaluate how signal processing affects cross-sensor correlation metrics.
• Experiment with thresholding schemes, wavelet families, decomposition levels, and multivariate techniques (e.g., PCA, VMD).
• Collaborate with an interdisciplinary team blending machine learning, signal processing, clinical insights, and systems thinking.
• Present findings and propose real-world use cases for improved signal integrity.
Ideal Candidate:
• Enrolled in a graduate or advanced undergraduate program in Electrical Engineering, Applied Mathematics, Statistics, or a related field.
• Strong foundation in signal processing, particularly time-frequency methods.
• Familiarity with wavelet transforms, denoising algorithms, and correlation analysis.
• Curious, self-directed, and excited to explore open-ended technical challenges with tangible outcomes.
• Track record of research publications
• Bonus: Interest in biomedical signals and pattern recognition in noisy environments
