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Phd Signal Processing Jobs in New York (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 ...

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 ...

Synaptrix Labs

Grant Writer (PhD)

New York, NY

... signal processing, and computational neuroscience, not just better hardware. Our mission is to ... We're looking for a full-time Grant Writer (PhD) to lead and support high-quality grant submissions ...

Synaptrix Labs

Grant Writer (PhD)

New York, NY · On-site

... signal processing, and computational neuroscience, not just better hardware. Our mission is to ... We're looking for a full-time Grant Writer (PhD) to lead and support high-quality grant submissions ...

Synaptrix Labs

Grant Writer (PhD)

New York, NY

... signal processing, and computational neuroscience, not just better hardware. Our mission is to ... We're looking for a full-time Grant Writer (PhD) to lead and support high-quality grant submissions ...

QCi

Senior Engineer, Quantum Algorithms

Hoboken, NJ · On-site

Write efficient, thread-safe code for concurrent hardware control and real-time signal processing ... Advanced degree (MS/PhD) in Computer Science, Physics, or Mathematics. * Experience with classical ...

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Phd Signal Processing information

What is a PhD signal processing professional?

PhD Signal Processing professionals are experts who have earned a Doctor of Philosophy (PhD) in the field of signal processing, which involves analyzing, modifying, and interpreting signals such as sound, images, and scientific measurements. They apply advanced mathematical and computational techniques to extract meaningful information from complex data. These specialists often work in research, academia, telecommunications, medical imaging, audio engineering, and other industries that require sophisticated data analysis. Their work is crucial in developing technologies like speech recognition, radar systems, and biomedical devices.

What are some common challenges faced by professionals in PhD-level signal processing roles and how can they be addressed?

PhD-level Signal Processing professionals often encounter challenges such as managing large, complex datasets and developing novel algorithms that balance accuracy and computational efficiency. Staying current with rapidly evolving technologies and research can also be demanding. These challenges are typically addressed through ongoing professional development, collaboration with multidisciplinary teams, and leveraging advanced computational tools. Regularly participating in conferences, workshops, and peer discussions can also help professionals overcome research hurdles and stay innovative in their field.

What are the key skills and qualifications needed to thrive as a PhD signal processing specialist?

To thrive as a PhD Signal Processing specialist, you need deep expertise in mathematics, statistical analysis, and advanced signal processing algorithms, underpinned by a doctoral degree in electrical engineering or a related field. Proficiency in MATLAB, Python, C++, and experience with simulation tools and machine learning frameworks are commonly required, along with publications or research experience. Strong analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These competencies are vital for designing innovative solutions, advancing research, and conveying complex findings to both technical and non-technical stakeholders.

What is the difference between Phd Signal Processing vs Signal Processing Engineer?

AspectPhd Signal ProcessingSignal Processing Engineer
Required CredentialsPhD in Signal Processing or related fieldBachelor's or Master's in Electrical Engineering, Computer Science, or related field
Work EnvironmentResearch labs, academia, R&D departmentsIndustry, technology companies, product development
Employer & Industry UsageUniversities, research institutions, some tech companiesTech firms, telecommunications, aerospace, defense
Common Search & ComparisonYesYes

The main difference between Phd Signal Processing and Signal Processing Engineer lies in their focus and credentials. A PhD typically involves advanced research, theoretical work, and academic or R&D roles, while a Signal Processing Engineer applies practical skills in industry to develop and implement signal processing solutions. Both roles require knowledge of signal processing concepts, but their work environments and career paths differ significantly.

What are popular job titles related to Phd Signal Processing jobs in New York? For Phd Signal Processing jobs in New York, the most frequently searched job titles are:
What job categories do people searching Phd Signal Processing jobs in New York look for? The top searched job categories for Phd Signal Processing jobs in New York are:
What cities in New York are hiring for Phd Signal Processing jobs? Cities in New York with the most Phd Signal Processing job openings:
Phd Signal Processing jobs near you
Infographic showing various Phd Signal Processing job openings in New York as of July 2026, with employment types broken down into 100% Full Time. Highlights an 95% In-person, and 5% Remote job distribution.

Signal Processing Engineer

Norbert Health

New York, NY • On-site

Full-time

Re-posted yesterday

Job description

The company
Norbert is building autonomous robots that deliver healthcare.
Our AI sensing platform mounts on mobile robots and does the work of a care team member-rounding on patients, capturing vitals without contact (FDA-cleared for pulse and respiratory rate, more in the pipeline), running assessments, documenting to the EMR, and escalating when something's wrong. Autonomously.
We're not building demos. We're deployed in real facilities today, monitoring hundreds of patients daily. We're solving one of healthcare's hardest problems: a global nursing shortage that will hit 40% by 2030.
We're a small, international team backed by top-tier VCs, with offices in Brooklyn and Paris. We ship things that matter.
The position
We're looking for a Signal Processing Engineer to join our algorithm and development team, working on remote vital sign monitoring from video. You'll develop and validate algorithms that extract clinical-grade physiological signals (heart rate, blood pressure, respiration) from camera data, working closely with computer vision engineers in our algorithm team.
What You'll Do:
  • Design and implement signal processing algorithms for extracting vital signs from video-based sensors (rPPG, rBP)
  • Develop real-time filtering, denoising, and feature extraction methods to achieve clinical-grade accuracy
  • Build validation pipelines comparing our video-based measurements against clinical reference devices (ECG, PPG, BP monitors)
  • Help design studies that ensure millisecond-level synchronization between video streams and reference sensors for accurate ground truth
  • Integrate with the computer vision pipeline (C++) to leverage multi-modal signal enhancement techniques
  • Architect cloud-based QA and automated verification systems for reproducible algorithm validation
  • Prototype algorithms in Python and C++ before deploying them on our production system

What We're Looking For:
  • 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 expertise in physiological signal processing (PPG, ECG, respiration, blood pressure)
  • Experience processing low-frequency physiological signals with challenging SNR characteristics
  • Proficiency in both Python (prototyping) and C++ (production integration)
  • Experience with spectral analysis, adaptive filtering, and time-domain methods for real-time applications
  • Ability to work independently, solve complex problems, and drive projects to completion
  • 5+ years industry experience developing signal processing algorithms for medical or physiological sensing applications (or equivalent with PhD)

Bonus Points:
  • Experience with contact-based and contactless vital sign measurement technologies
  • Background working with medical-grade measurement devices and clinical reference standards
  • Experience with embedded signal processing (ARM, edge devices)
  • Knowledge of motion artifact removal and noise reduction in challenging environments
  • Familiarity with DevOps practices for reproducible research (experiment tracking, data versioning)
  • Background in medical devices, regulated environments, or clinical validation studie

What We Offer:
  • Real impact: your code provides care for patients today
  • High autonomy and technical ownership - you'll define our signal processing approach
  • Work at the intersection of cutting-edge AI, edge computing, and healthcare
  • A talented, excellent, diverse and international team
  • Talented, international team tackling meaningful problems in healthcare
  • Equity participation in the company's future
  • Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing
  • Transparent, mission-driven culture focused on continuous learning
  • Competitive salary and equity

Apply