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Biomedical Signal Processing Postdoctoral Jobs (NOW HIRING)

Norbert Health

Signal Processing Engineer

New York, NY · On-site

Master's degree in Electrical Engineering, Biomedical Engineering, or related field (or PhD) * Strong fundamentals in digital signal processing, statistical methods, and real-time systems * Deep ...

CoVar

Signal Processing Engineer

Durham, NC

Signal Processing Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... We develop AI/ML tools to help the DoD detect enemies and threats, help biomedical researchers find ...

Norbert Health

Signal Processing Engineer

Brooklyn, NY · On-site

Master's degree in Electrical Engineering, Biomedical Engineering, or related field (or PhD) * Strong fundamentals in digital signal processing, statistical methods, and real-time systems * Deep ...

Norbert Health

Signal Processing Engineer

New York, NY · On-site

Master's degree in Electrical Engineering, Biomedical Engineering, or related field (or PhD) * Strong fundamentals in digital signal processing, statistical methods, and real-time systems * Deep ...

Masimo Wearables

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$110K - $152K/yr

They are seeking a Sr Engineer in AI/Machine Learning to develop advanced algorithms and models for biomedical signal processing, working closely with cross-functional teams to enhance product ...

Masimo

Sr Engineer II, Algorithm (ECG)

Irvine, CA · On-site

$139K - $185K/yr

... biomedical signal processing, including significant hands-on ECG waveform analysis experience. * Deep expertise in digital signal processing, statistical modeling, and algorithm optimization.

Masimo

Sr Engineer II, Algorithm (ECG)

Irvine, CA · On-site

$139K - $185K/yr

... biomedical signal processing, including significant hands-on ECG waveform analysis experience. * Deep expertise in digital signal processing, statistical modeling, and algorithm optimization.

Rutgers University

Postdoctoral Associate

Piscataway, NJ · On-site

... Rutgers Biomedical and Health Sciences (RBHS) takes an integrated approach to educating students ... Performs advanced signal processing and time-frequency analyses of neural recordings. * Develops ...

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How much do biomedical signal processing postdoctoral jobs pay per year?

As of Jun 4, 2026, the average yearly pay for biomedical signal processing postdoctoral in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Biomedical Signal Processing Postdoctoral researcher, and why are they important?

To thrive as a Biomedical Signal Processing Postdoctoral researcher, you need a Ph.D. in biomedical engineering, electrical engineering, or a related field, with strong expertise in signal processing and data analysis. Proficiency in programming languages such as MATLAB or Python and experience with specialized software like LabVIEW or EEGLAB are typically required. Excellent problem-solving skills, teamwork, and effective communication set top candidates apart in collaborative research environments. These skills and qualifications are essential for advancing innovative research, efficiently analyzing complex biomedical data, and contributing to multidisciplinary teams.

What are some common interdisciplinary collaborations for a Biomedical Signal Processing Postdoctoral researcher?

Biomedical Signal Processing Postdoctoral researchers frequently collaborate with clinicians, biomedical engineers, computer scientists, and statisticians. These partnerships are essential for acquiring high-quality physiological data, interpreting clinical requirements, and developing robust signal analysis algorithms. Working in multidisciplinary teams helps ensure research outcomes are both scientifically rigorous and clinically applicable, providing valuable experience in translating technical solutions to real-world healthcare problems.

What is a Biomedical Signal Processing Postdoctoral researcher?

A Biomedical Signal Processing Postdoctoral researcher is a scientist who has completed their Ph.D. and conducts advanced research in analyzing biological signals, such as EEG, ECG, or MRI data, often using computational and statistical methods. Their work typically involves developing new algorithms and tools to process, interpret, and extract meaningful information from complex biomedical data. These researchers often collaborate with clinicians and engineers to improve medical diagnostics, monitoring, and treatment. Their role is crucial in advancing healthcare technologies and understanding physiological processes.

What is the difference between Biomedical Signal Processing Postdoctoral vs Biomedical Data Analyst?

AspectBiomedical Signal Processing PostdoctoralBiomedical Data Analyst
Required CredentialsPhD in Biomedical Engineering, Signal Processing, or related fieldBachelor's or Master's in Data Science, Bioinformatics, or related field; sometimes PhD
Work EnvironmentResearch labs, universities, academic institutionsHospitals, healthcare companies, research organizations
Employer & Industry UsageAcademic research, grants, university projectsHealthcare analytics, biotech firms, clinical data analysis

The Biomedical Signal Processing Postdoctoral role focuses on advanced research in signal analysis, often within academic settings, requiring a PhD. In contrast, a Biomedical Data Analyst applies data analysis skills to healthcare data in industry environments, often with a bachelor's or master's degree. Both roles involve working with biomedical data but differ in their focus, environment, and credential requirements.

Data Scientist - Biomedical Signal Processing

Sphere Software

Manhattan, NY • Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Position: Data Scientist / Machine Learning Engineer Client: AI-Driven HealthTech / Biosignal Analytics Product Engagement Type: Consulting → Potential Phase 3 Implementation Location: Remote Role Overview We are looking for a Data Scientist / ML Engineer with a biomedical signal processing background to support development of real-time AI solutions based on physiological signals . The role begins with consulting , followed by hands‐on model training and optimization during Phase 3 of product development . The ideal candidate has experience working with messy physiological datasets , including ECG, EEG, EOG, brain waves, or other low‐frequency biosignals , and is comfortable building end‐to‐end ML pipelines — from signal filtering and feature engineering to real‐time model deployment .

Key Responsibilities Phase 1–2: Consulting & Architecture Analyze physiological signal datasets and data quality Recommend signal preprocessing and filtering strategies Define feature engineering approach for biosignals Suggest model architecture for real‐time predictions Advise on data pipeline and training strategy Help define evaluation metrics and validation approach Phase 3: Model Training & Implementation Process low‐frequency physiological signals (ECG, EEG, brain waves, biosignals) Apply signal filtering, noise reduction, and transformations Build feature extraction pipelines from physiological data Train and optimize machine learning models Support real‐time inference and model performance optimization Work closely with engineering team for model integration Improve model accuracy through experimentation and iteration Required Experience 2+ years experience as Data Scientist / ML Engineer / Biomedical Data Scientist Strong signal processing background Experience working with physiological or biomedical signals such as: ECG EEG EOG Brain waves Other biosignals Experience working with low‐frequency signals Experience handling noisy or heterogeneous physiological datasets Hands‐on experience with: Signal filtering Mathematical filters Feature extraction Time‐series analysis Python skills: NumPy SciPy Pandas Scikit‐learn Nice to Have Biomedical engineering background Neuroimaging or electrophysiology experience Experience working with multi‐source physiological datasets Experience building reproducible research pipelines Experience with real‐time ML solutions PyTorch / TensorFlow experience Engagement Model Phase 1–2: Consulting / Advisory Phase 3: Model Training & Implementation Real‐time biosignal AI product #J-18808-Ljbffr

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