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Neural Signal Processing Phd Jobs (NOW HIRING)

Neuralink

Signal Processing Engineer

Austin, TX · On-site

$121K - $230K/yr

Design and develop signal processing algorithms for sensing neural activity in the cortex (e.g ... Education : BS, MS or PhD in Electrical Engineering, Computer Engineering, Signal Processing, or a ...

Neuralink

Signal Processing Engineer

Austin, TX · On-site

$121K - $230K/yr

Design and develop signal processing algorithms for sensing neural activity in the cortex (e.g ... Education : BS, MS or PhD in Electrical Engineering, Computer Engineering, Signal Processing, or a ...

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

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 ...

Cypress HCM

Signal Processing Engineer

Redwood City, CA

$150 - $190K/hr

Signal Processing Engineer Location: Belmont, CA (hybrid) Employees : Industry : Wireless services ... PhD in Electrical Engineering, or equivalent research experience, specializing in wireless ...

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Neural Signal Processing Phd information

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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.

Signal Processing Engineer

Austin, TX • On-site

Neuralink
Biotechnology Research and Development • 201 - 500 employees
Learn more about Neuralinkexternal

$121K - $230K/yr

Full-time

Re-posted 12 days ago

Job description

Job Summary

We are seeking a talented Signal Processing Engineer to design, develop, and optimize advanced digital signal processing (DSP) algorithms for on-chip and embedded implementation. In this role, you will create efficient, hardware-friendly algorithms that run directly on custom SoCs, enabling real-time processing with constraints on power, latency, area, and throughput. You will collaborate closely with the SoC, Firmware, and Machine Learning teams to translate high-level signal processing needs into production-ready solutions.

Key Responsibilities
  • Design and develop signal processing algorithms for sensing neural activity in the cortex (e.g. spike detection), monitoring cortical electrode health, and more.
  • Design and develop numerical algorithms, such as custom data compression to increase radio throughput.
  • Develop fixed-point or quantized versions of algorithms optimized for constrained hardware.
  • Implement and verify algorithms in high-level languages and transition them to hardware-friendly representations.
  • Perform algorithm-to-architecture mapping: analyze trade-offs between accuracy, latency, power, and resource utilization on the SoCs.
  • Collaborate with the digital design team to define micro-architectures for custom on-chip processing pipelines, including dataflow, pipelining, and parallelization.
Required Qualifications
  • Education: BS, MS or PhD in Electrical Engineering, Computer Engineering, Signal Processing, or a related field.
  • Experience: 3+ years in digital signal processing algorithm development or real-world products, with a focus on embedded or hardware-constrained implementations.
  • Fluent in signal processing fundamentals (both analog and digital) and strong numerical capabilities.
  • Familiarity with fixed-point arithmetic, quantization effects, and numerical precision trade-offs.
  • Proficiency in Python and C for algorithm prototyping and simulation.
Preferred Qualifications
  • Hands-on experience with Verilog/VHDL, or transitioning algorithms to RTL.
  • Experience with dedicated DSP cores or accelerators.
  • Track record of optimizing for power/area/latency in resource-constrained environments.

Expected Compensation:

The anticipated base salary for this position is expected to be within the following range. Your actual base pay will be determined by your job-related skills, experience, and relevant education or training. We also believe in aligning our employees' success with the company's long-term growth. As such, in addition to base salary, Neuralink offers equity compensation (in the form of Restricted Stock Units (RSU)) for all full-time employees.

Base Salary Range:

 $121,000 - $230,500

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