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Deep Learning Eeg Jobs (NOW HIRING)

NextSense

Senior ML/Research Scientist

Mountain View, CA · On-site +1

$116K - $148K/yr

... deep learning, advanced statistics, and data visualization * Excellent written, verbal ... Comfortable conducting conventional and mobile EEG recordings or willing to learn * Experience with ...

ApplyMint

Software Research Engineer

Manhattan, NY · On-site

$226K/yr

Hands-on experience with a deep learning framework (PyTorch or equivalent) for both training and ... Experience decoding neural or biomedical time series - intracortical, ECoG, EEG, EMG, or other ...

UNC Health

Pediatrics Physician

Morrisville, NC · On-site

$159K - $205K/yr

... learning, and personal and professional sustainability. Through close partnership with UNC Health ... Deep brain stimulation (DBS) for pediatric patients * Working knowledge of high density scalp EEG ...

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How much do deep learning eeg jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for deep learning eeg in the United States is $34.48, according to ZipRecruiter salary data. Most workers in this role earn between $26.44 and $40.38 per hour, depending on experience, location, and employer.

What is a deep learning EEG specialist?

A Deep Learning EEG specialist is a professional who applies deep learning techniques to analyze and interpret electroencephalogram (EEG) data. These experts work at the intersection of neuroscience, data science, and artificial intelligence, developing algorithms to detect patterns in brainwave signals for purposes such as diagnosing neurological disorders, brain-computer interfacing, or cognitive research. Their role often involves preprocessing raw EEG data, designing and training neural networks, and collaborating with clinicians or researchers to translate findings into practical applications.

What are the key skills and qualifications needed to thrive as a deep learning EEG specialist?

To thrive as a Deep Learning EEG Specialist, you need expertise in neuroscience or biomedical engineering, strong programming skills (Python), and a solid understanding of deep learning algorithms and EEG signal processing. Familiarity with machine learning frameworks like TensorFlow or PyTorch, experience with EEG analysis software (e.g., EEGLAB or MNE), and often a relevant graduate degree are typically required. Strong analytical thinking, problem-solving ability, and clear communication are crucial soft skills for collaborating with interdisciplinary teams and conveying complex results. These skills are vital for developing accurate, innovative models that advance EEG-based research and applications in healthcare or neuroscience.

What are some common challenges faced by deep learning EEG specialists when working with neurological data?

Deep Learning EEG specialists often encounter challenges such as managing large volumes of noisy and artifact-prone data, ensuring accurate labeling for training models, and addressing variability across subjects. Additionally, bridging the gap between model interpretability and clinical relevance can be complex, as stakeholders such as clinicians may require clear explanations of AI-driven findings. Collaboration with neuroscientists, clinicians, and data engineers is common to refine models and ensure the robustness and applicability of results in real-world healthcare settings.

What is the difference between Deep Learning Eeg vs Machine Learning Engineer?

AspectDeep Learning EegMachine Learning Engineer
Required CredentialsBackground in neuroscience, signal processing, deep learningComputer science, data science, programming skills
Work EnvironmentResearch labs, healthcare, neuroscience settingsTech companies, data-driven industries, software development
Industry UsageNeuroscience, medical diagnostics, brain-computer interfacesFinance, tech, healthcare, e-commerce

Deep Learning Eeg specialists focus on analyzing EEG data using deep learning techniques within neuroscience and healthcare contexts. In contrast, Machine Learning Engineers develop algorithms across various industries, often working with diverse data types. While both roles require programming and data analysis skills, Deep Learning Eeg roles emphasize neuroscience knowledge and signal processing, making them more specialized in brain data analysis.

What other helpful pages are available for Deep Learning Eeg?

Other pages related to Deep Learning Eeg:

Infographic showing various Deep Learning Eeg job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $71,720 per year, or $34.5 per hour.

Senior ML/Research Scientist

Mountain View, CA • On-site, Remote

NextSense
Medical Equipment and Supplies Manufacturing • 11 - 50 employees
Learn more about NextSenseexternal

$116K - $148K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 16 days ago

Job description

Company Description
About NextSense:
NextSense's vision is to be the foundation of brain health and establish a new paradigm in neurocare. Powered by a disruptive brain-sensing earbud technology and digital ecosystem, our mission is to establish new ways of diagnosing and optimizing therapy for diverse neurological conditions. We hope to unlock brain health for everyone with real world data insights and practical, scientific wisdom for daily living.
Job Description
About the Job:
As a ML/Research Scientist, you will play a crucial role in developing next-generation wearable neurotechnologies. You will design, implement, and lead innovative research to develop novel digital biomarkers and applications for various neurological conditions. You will work with industry partners and academic leaders on clinical trials and collaborative research projects. You will collaborate with an interdisciplinary team of scientists, medical specialists, HW/SW engineers, and product managers to translate fundamental scientific knowledge into clinical and consumer products.
Responsibilities:
  • Design, execute, and present cutting-edge research to advance our biosensing earbud technology.
  • Apply signal processing, machine learning, and statistical analysis to decode biosignals.
  • Develop algorithms for automated detection of healthy and pathological neural signatures
  • Contribute to the implementation of data analysis pipelines for large-scale physiological signals from clinical studies.
  • Collect, analyze, and interpret data for pilot and clinical studies.
  • Collaborate with engineering and product teams to integrate the latest research into prototypes and products.
  • Assist in writing peer-reviewed publications and conference abstracts.
  • Engage in building tools, libraries, or processes that are used throughout the company or in the open-source community.

Qualifications
Minimum Qualifications:
  • Masters in computational neuroscience, systems neuroscience, bioengineering, bioinformatics, computer science, electrical engineering, or related fields/experience
  • Strong Python programming skills; ability to demonstrate mastery through work experience or personal projects
  • Strong technical skills associated with biosignal time-series analysis, including signal processing, machine/deep learning, advanced statistics, and data visualization
  • Excellent written, verbal, interpersonal communication, and presentation skills
  • Passionate about neurotechnologies and their potential to benefit society

Preferred Qualifications:
  • 5+ years industry experience
  • Comfortable conducting conventional and mobile EEG recordings or willing to learn
  • Experience with cloud-based platforms (GCP preferred)
  • Ability to strive in a fast-paced startup environment
  • Demonstrated productive publishing record
  • Experience with version control (e.g., Git)

Additional Information
Benefits:
  • Our careers benefits include but are not limited to the following:
  • Flexible/hybrid work schedule (built-in work from home days)
  • Equity
  • Retirement savings (no employer matching at this stage)
  • Healthcare Flexible Spending Account (FSA)
  • Medical, dental, vision, and life insurance
  • Wellness-bundle, commuter benefits
  • Paid vacation, holidays, parental leave

Location:
Mountain View, CA (not a remote position)
Employment Eligibility:
At this time NextSense is only considering candidates for this role who are eligible to legally work in the US without any Visa sponsor/transfer requirements now or in the future. Eligible candidates who can work on a TN Visa from Mexico or Canada will be considered.

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