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Neural Interface Research Jobs (NOW HIRING)

Neuralink

Software Engineer, Next Gen

Austin, TX · On-site

... neural interfaces and other data acquisition systems to decode and modulate brain activity. We are ... Working with neuroengineers and animal training specialists to support research sessions Required ...

University of Colorado

Senior Research Scientist

Aurora, CO · On-site

$100K - $127K/yr

... interface, and intraoperative task design to support Dr. Daniel Kramer's laboratory work. The ... Experience with machine learning and neural decoding approaches * Experience integrating and ...

Neuralink

Software Engineer, Next Gen

Austin, TX · On-site

$151K - $281K/yr

... neural interfaces and other data acquisition systems to decode and modulate brain activity. We are ... Working with neuroengineers and animal training specialists to support research sessions Required ...

University of Michigan

RESEARCH FELLOW

Ann Arbor, MI · On-site

... brain machine interface technology. The role involves comprehensive testing of chronically ... Specific aspects of the position include chronic microelectrode implantation surgery, neural ...

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

You will work closely with leading experts in neural decoding and AI to push the boundaries of what is possible in brain-computer interfaces. This role sits at the intersection of ambitious research ...

Devyantram

Lead Biohybrid Systems Engineer

Ashburn, VA · On-site

$145K - $165K/yr

Strongly Preferred • Organic bioelectronics, iontronics, or neuromorphic materials. • Organoid, neural-tissue, or biohybrid-computing research. • Bioelectronic interfaces, neural probes, or ...

Tacit

Machine Learning Scientist

San Francisco, CA · On-site

$180K - $270K/yr

This position spans foundational research in deep learning, hands-on model development, and ... neural interfaces. * Hands-on experience with consumer wearables or custom hardware. * Knowledge of ...

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Neural Interface Research information

What is neural interface research?

Neural interface research is the scientific study and development of technologies that connect the nervous system, particularly the brain, with external devices or computers. These interfaces, often called brain-computer interfaces (BCIs) or neural prosthetics, enable direct communication between neural tissue and electronic systems. The goal of this research is to restore lost sensory or motor functions, treat neurological disorders, or enhance human capabilities. Neural interface research is highly interdisciplinary, involving neuroscience, engineering, computer science, and medicine. Advances in this field have the potential to revolutionize healthcare and human-machine interaction.

What are the key skills and qualifications needed to thrive in neural interface research?

To thrive in Neural Interface Research, you need advanced knowledge in neuroscience, biomedical engineering, and signal processing, often supported by a graduate degree in a related field. Proficiency with programming languages (such as Python or MATLAB), neural data acquisition systems, and simulation tools is typically required. Exceptional problem-solving abilities, collaboration, and strong communication skills help researchers innovate and translate findings across multidisciplinary teams. These skills are crucial for developing cutting-edge neural technologies and ensuring rigorous, impactful scientific progress.

What are some common interdisciplinary challenges faced by professionals in neural interface research teams?

Neural Interface Research teams often bring together experts from neuroscience, engineering, computer science, and clinical backgrounds, which can lead to challenges in communication and aligning goals across disciplines. Collaborators may use different terminology or have varying expectations regarding project timelines and outcomes. Successful professionals in this field need to be proactive in fostering clear communication, demonstrating adaptability, and developing a basic understanding of adjacent fields to effectively contribute to collaborative projects. These interdisciplinary challenges ultimately offer valuable opportunities for personal growth and innovation.

What is the difference between Neural Interface Research vs Neural Engineering?

AspectNeural Interface ResearchNeural Engineering
Required CredentialsAdvanced degrees in neuroscience, biomedical engineering, or related fieldsSimilar credentials, often with additional focus on device design and implementation
Work EnvironmentResearch labs, universities, biotech companiesResearch labs, medical device companies, clinical settings
Industry UsageFocuses on developing and understanding neural interfacesDesigning, testing, and applying neural interface devices
Common Search IntentResearch methods, latest advancements, academic rolesProduct development, device engineering, clinical applications

Neural Interface Research primarily involves exploring and understanding neural interfaces through scientific investigation, while Neural Engineering focuses on designing and developing neural interface devices for practical use. Both roles require similar educational backgrounds but differ in their application and work environment.

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Neural Interface Research jobs near you
Infographic showing various Neural Interface Research job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Research Scientist, Artificial Intelligence (PhD)

New York, NY • On-site

Synaptrix Labs
See more jobs at Synaptrix Labsexternal

$85K - $150K/yr

Full-time

PTO

Re-posted 28 days ago

Job description

About Synaptrix Labs Inc.
Synaptrix is on a mission to revolutionize brain-computer interfaces through non-invasive approaches. We believe that the power to diagnose and treat neurological conditions safely, and to expand human potential, will become a reality with the right fusion of deep learning, signal processing, and computational neuroscience.
We're seeking a full time Research Scientist, Artificial Intelligence (PhD) to join our growing team of researchers & engineers. If you're passionate about shaping the future of brain-computer interfaces and excited by the potential of deep learning in neurotechnology, we want to hear from you!
Responsibilities:
  • Design, prototype, and optimize state-of-the-art AI systems for neural decoding, including diffusion models, graph neural networks, contrastive/self-supervised frameworks, and transformer-based sequence models.
  • Conduct foundational research on neural time-series representation learning: build architectures that extract latent dynamics from EEG, EMG, or related biosignals.
  • Develop high-fidelity simulation environments for testing decoding algorithms, incorporating stochastic signal noise and realistic biophysical constraints.
  • Scale model training across multi-GPU and multi-node clusters using PyTorch Distributed, DeepSpeed, or JAX/Flax; profile and tune system performance for sub-10 ms inference latency.
  • Build and maintain end-to-end research pipelines for large-scale signal datasets, including preprocessing, artifact rejection, and multimodal fusion with video, audio, and IMU data.
  • Collaborate with neuroscientists and hardware engineers to integrate learned models into real-time BCI control loops and embedded systems.
  • Contribute to core ML infrastructure: experiment tracking, model versioning, dataset lineage, and reproducibility standards.
  • Publish at top-tier ML or neurotech venues (NeurIPS, ICLR, Nature Neuro, EMBC) and present findings to the research community.

Minimum Qualifications:
  • PhD or equivalent deep technical expertise in Machine Learning, Artificial Intelligence, Computer Science, Computational Neuroscience, or related fields.
  • Strong command of PyTorch or JAX, with experience implementing custom training loops, loss functions, and model architectures.
  • Proven ability to conduct end-to-end research, from conceptual design to reproducible experiments and evaluation.
  • Strong mathematical foundations in linear algebra, probability, optimization, and information theory.
  • Experience working with high-dimensional time-series or sensory data (EEG, speech, video, motion capture, etc.).
  • Skilled in Python, NumPy, Pandas, and scientific computing workflows; experience with CUDA or low-level GPU debugging is highly valued.
  • Demonstrated ability to operate independently on open-ended problems and drive original research with limited supervision.

Preferred Qualifications:
  • Deep familiarity with neural signal modeling, neural decoding, or biosignal preprocessing (EEG/MEG/ECoG/EMG).
  • Experience designing self-supervised or generative models (diffusion, VAEs, contrastive, masked modeling) for noisy, non-stationary data.
  • Background in reinforcement learning, optimal control, or human-in-the-loop systems, especially in continuous domains.
  • Publications or preprints in top venues (NeurIPS, ICML, ICLR, CVPR, EMBC, Nature Neuro).
  • Familiarity with distributed training, mixed-precision, multi-GPU orchestration, and cloud ML infrastructure (AWS/GCP/Azure).
  • Contributions to open-source ML frameworks or custom CUDA kernels.
  • Understanding of neural signal acquisition hardware, embedded inference, or edge ML deployment.
  • Track record of curiosity-driven, independent research resulting in practical systems or open-source codebases.

About our Culture:
At Synaptrix Labs, we celebrate curiosity, open collaboration, and scientific rigor. Our interdisciplinary team spans neuroscience, AI, and clinical research, and we are united by the belief that non-invasive BCI is the key to unlocking a new era in healthcare, accessibility, and human augmentation.
Expected Compensation:
The base salary for this role is anticipated to fall within the following range. Actual compensation will depend on your experience, technical expertise, and relevant education or training. In addition to base pay, Synaptrix offers equity to all full-time employees, reflecting our commitment to shared success and long-term company growth.
Base Salary Range:
$85,000 - $150,000 USD
What We Offer:
  • An opportunity to change the world and work with some of the smartest and most talented experts from different fields
  • Growth potential; we rapidly advance team members who have an outsized impact
  • Paid holidays, unlimited PTO

Apply