ZipRecruiter

Log In

1

Neural Signal Processing Phd Jobs (NOW HIRING)

Mantis Robotics

Master's or PhD degree in a related engineering field, including but not limited to electrical engineering, signal processing, computer science, or physics * Prior experience in algorithm and/or ...

Huntington Ingalls Industries

$90K - $114K/yr

Develop system concepts and signal processing algorithms * Work as part of a small team to ... PhD in related field; or High School Diploma or equivalent and 9 years relevant experience.

HII's Mission Technologies division

$90K - $114K/yr

Develop system concepts and signal processing algorithms * Work as part of a small team to ... PhD in related field; or High School Diploma or equivalent and 9 years relevant experience.

Vanteon Corp

NY · On-site

$150K - $175K/yr

PhD in Communications and Signal Processing (or be in candidacy) * 5+ years of experience in digital signal processing design (or related academic research) Other Requirements * Training and regular ...

HII's Mission Technologies division

$112K - $151K/yr

... with PhD or Juris Doctorate in related field; or High School Diploma or equivalent and 13 years ... Implement or maintain signal processing algorithms written in C/C++, Python or MATLAB * Ability to ...

previous page

Showing results 41-60

All JobsHealthcare JobsMedical Research JobsClinical Research Manager JobsNeural Signal Processing Phd Jobs

Neural Signal Processing Phd information

See salary details

$53.5K

$131.3K

$193.5K

How much do neural signal processing phd jobs pay per year?

As of Sep 10, 2026, the average yearly pay for neural signal processing phd in the United States is $131,349.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $147,500.00 per year, depending on experience, location, and employer.

What is a neural signal processing PhD?

A Neural Signal Processing PhD is a doctoral-level qualification focused on the analysis, interpretation, and modeling of electrical signals generated by the nervous system. Researchers in this field use advanced mathematical, computational, and engineering techniques to study brain activity, develop brain-computer interfaces, and improve understanding of neural function. Graduates typically contribute to neuroscience, biomedical engineering, medical device development, or academic research. The program often involves interdisciplinary work, combining neuroscience, electrical engineering, computer science, and applied mathematics.

What are some typical interdisciplinary collaborations for a neural signal processing PhD in an academic or industry setting?

Neural Signal Processing PhDs often work closely with neuroscientists, computer scientists, biomedical engineers, and clinicians. In both academia and industry, you may collaborate with teams developing brain-computer interfaces, analyzing clinical EEG/MEG data, or designing neural prosthetics. These collaborations allow you to contribute your expertise in signal processing while gaining insights from other fields, leading to innovative solutions for complex neural data challenges. Regular meetings, joint publications, and cross-functional project work are common in these collaborative environments.

What are the key skills and qualifications needed to thrive as a neural signal processing PhD, and why are they important?

To excel as a Neural Signal Processing PhD, you need advanced knowledge in neuroscience, signal processing, and mathematics, supported by a doctoral degree in a relevant field. Expertise with programming languages like Python or MATLAB, experience with neural recording systems, and familiarity with data analysis software are typically required. Strong analytical thinking, problem-solving, and collaboration skills help you interpret complex data and work effectively in multidisciplinary research teams. These skills are crucial for advancing neuroscientific understanding and developing innovative solutions for brain-computer interfaces or neurological disorders.

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

AspectNeural Signal Processing PhdNeural Engineer
Required CredentialsPhD in neuroscience, engineering, or related fieldBachelor's or master's in engineering, neuroscience, or related field
Work EnvironmentResearch labs, academia, industry R&DProduct development, hardware/software design, clinical settings
Industry UsageAcademic research, biotech, neurotechnology companiesMedical device companies, neurotechnology firms, startups

The Neural Signal Processing Phd typically focuses on advanced research, data analysis, and developing new algorithms for neural data. In contrast, a Neural Engineer often applies engineering principles to develop neurotechnology products and devices. While both roles require a strong background in neural systems, the Phd emphasizes research and theory, whereas the Neural Engineer emphasizes practical application and product development.

What are popular job titles related to Neural Signal Processing Phd jobs?

For Neural Signal Processing Phd jobs, the most frequently searched job titles are:

Infographic showing various Neural Signal Processing Phd job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 93% In-person, and 7% Hybrid job distribution, with an average salary of $131,349 per year, or $63.1 per hour.

Radar Signal Processing Engineer

On-site

Mantis Robotics
Industrial Automation Equipment Manufacturing • 1 - 10 employees
Learn more about Mantis Roboticsexternal

Other

Posted 9 days ago

Key responsibilities

  • Develop radar algorithms for object tracking, classification, environmental modeling, and sensor fusion.

  • Conduct testing of radar signal processing algorithms using real-world data and validate their performance.

  • Document algorithm designs, implementation details, testing procedures, and create API documentation and user manuals.

Job description

Mantis Robotics is building the fastest and safest industrial robots that can work safely with people, to make robotic automation accessible to anyone wanting to automate a manual task. Mantis Robotics BV (Leuven) is the Belgian R&D centre of Silicon Valley based Mantis Robotics Inc, one of the fastest growing robotics startups, backed by Amazon (lead investor).

We are seeking a highly skilled and motivated radar signal processing engineer to join our sensor development team in Leuven, Belgium. The selected candidate will play a critical role in designing, developing, and validating various features of our radar processing algorithms.

We are committed to respect, transparency, honesty, integrity, fairness and customer focus.

CORE RESPONSIBILITIES:
  • Your primary responsibility will be the development of our dedicated radar algorithms for object tracking and classification, environmental modeling, and sensor fusion to ensure high performance without compromising safety constraints. To achieve our objectives, we expect you to:
  • collaborate with cross-functional engineering teams and research groups to decide on requirements, architecture and validation methods
  • develop tools and data visualization techniques to effectively gain insights into the performance and physical boundaries of our radar system
  • conduct thorough testing of radar signal processing algorithms using real-world data, representing standard conditions and corner cases
  • document algorithm designs, implementation details, and testing procedures, and create API documentation and user manuals for our software developers
  • support integration and test, evaluate test results, investigate discrepancies, provide technical assessment of anomalies, and drive issues to resolution
QUALIFICATIONS:
  • Master’s or PhD degree in a related engineering field, including but not limited to electrical engineering, signal processing, computer science, or physics
  • Prior experience in algorithm and/or software development for radar applications, demonstrating fundamental knowledge of the related theoretical framework of radar signal processing (e.g., contested spectrum, beamforming, and direction-of-arrival estimation)
  • Proficiency in statistical concepts, mathematical modeling, and data interpretation (e.g., linear and logistic regression, Bayesian techniques)
  • Experience with RF signature recognition and classification algorithms
  • Experience with computational imaging and image reconstruction techniques
  • Experience in C/C++ programming, preferably on embedded devices, and familiarity with Python
  • Strong written and verbal communication skills in English
PREFERRED:
  • Prior experience developing sensor fusion algorithms using data from different sensing modalities including radar, camera, and ToF/LiDAR systems.
  • Experience with version control tools such as Git, SVN or equivalents
  • Knowledge of radar firmware development is advantageous
  • Experience in the development and management of research projects

Mantis Robotics is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status.

#J-18808-Ljbffr

Apply