About Synaptrix Labs Inc.

Synaptrix is building the future of non-invasive brain-computer interfaces.

We believe the next leap in neurotechnology will come from the right fusion of deep learning, signal processing, and computational neuroscience, not just better hardware. Our mission is to build systems that can restore communication, mobility, and autonomy, while laying the foundation for a new era of human-computer interaction.

We’re looking for a full-time Grant Writer (PhD) to lead and support high-quality grant submissions across NIH, NSF, DoD, BARDA, ARPA-H, and other non-dilutive funding programs. This person will work closely with leadership, research, and technical teams to help Synaptrix secure funding that accelerates both our science and product roadmap.

Responsibilities:

• Lead drafting and submission of grants across NIH, NSF, DoD, ARPA-H, and related agencies
• Translate Synaptrix’s technical work into clear, compelling, fundable proposals
• Manage the full grant lifecycle: opportunity identification, writing, submission, revisions, and reporting
• Work closely with leadership, scientists, and engineers to shape specific aims, technical narratives, milestones, and budgets
• Help structure research roadmaps around grantable workstreams and strategic funding opportunities
• Support subcontractor / academic collaborator coordination when relevant
• Maintain a pipeline of upcoming non-dilutive funding opportunities relevant to Synaptrix

Minimum Qualifications:

• PhD in Neuroscience, Biomedical Engineering, Computer Science, Bioengineering, or related field
• Strong experience writing and/or supporting successful NIH, NSF, DoD, or equivalent federal grant submissions
• Excellent scientific and technical writing skills
• Ability to understand and communicate complex interdisciplinary work across AI, neurotechnology, signal processing, and medical devices
• Highly organized and able to independently manage multiple deadlines and submissions
• Strong judgment, ownership, and attention to detail

Preferred Qualifications:

• Prior experience in neurotechnology, BCI, computational neuroscience, medical devices, or translational biotech
• Familiarity with SBIR/STTR, R01/R21, NSF translational grants, or defense-related funding mechanisms
• Experience working directly with startup founders, principal investigators, or technical R&D teams
• Comfort contributing to scientific strategy, framing research directions in ways that are both ambitious and fundable
• Experience with grant reporting, progress updates, and compliance documentation

About our Culture:

We care a lot about talent density, speed, and intellectual honesty.

Synaptrix is a small, ambitious team working on a problem that actually matters. We value people who can think clearly, write sharply, move fast, and operate with high ownership. We are deeply mission-driven, highly technical, and serious about building something important.

What We Offer:

• Competitive pay + equity
• Health benefits
• A chance to help shape the future of neurotechnology and non-invasive BCI
• High ownership and direct exposure to company strategy, research, and fundraising
• Growth potential for team members who have outsized impact
• Paid holidays, unlimited PTO

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 passionate, creative, and technically driven interns to join our team across multiple disciplines: Software Engineering, Hardware Engineering, Machine Learning Research, Industrial Design, and UI/UX Design. If you’re excited about building the future of brain-computer interfaces and want to work at the intersection of neuroscience, AI, and human experience, we want to hear from you.

Responsibilities:

Depending on your background and interests, you may:

• Contribute to development of real-time software systems for neural signal processing and data visualization.
• Build and prototype non-invasive EEG-based BCI hardware, from electrode arrays to embedded microcontroller systems.
• Design, train, and evaluate machine learning models for EEG/EMG decoding, denoising, and signal enhancement.
• Develop intuitive interfaces and user experiences for individuals with mobility or communication impairments.
• Collaborate with the design team to prototype wearable and ergonomic form factors for next-generation neurotech devices.
• Support data collection and analysis in research sessions, assisting with experimental setup and instrumentation.
• Participate in cross-functional design reviews and brainstorming sessions that bring together neuroscience, AI, and engineering.
• Contribute to internal documentation, test plans, and experimental logs for ongoing R&D projects.

Minimum Qualifications:

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Biomedical Engineering, Neuroscience, Mechanical/Industrial Design, or a related field.
• Demonstrated experience with one or more of the following:
  • Software: Python, C++, or JavaScript
  • Machine Learning: PyTorch, TensorFlow, or JAX
  • Hardware: Arduino, PCB design, or embedded systems
  • Design: Figma, Fusion 360, SolidWorks, or similar tools
• Strong problem-solving ability and curiosity about neuroscience, AI, or human-machine interfaces.
• Excellent communication and teamwork skills; thrives in a fast-paced, interdisciplinary environment.
• Availability for an internship in New York City.

Preferred Qualifications:

• Prior experience with EEG/EMG systems, biosignal acquisition, or data analysis.
• Familiarity with deep learning for time-series or multimodal data.
• Experience designing assistive devices, wearables, or medical technology.
• Portfolio, GitHub, or research projects demonstrating creative technical work.
• Interest in startups, prototyping, and early-stage innovation.

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.

As an intern, you’ll work directly alongside engineers, researchers, and designers who are defining the next generation of brain-computer interfaces. You’ll be encouraged to explore bold ideas, experiment freely, and take ownership of meaningful projects from day one.

What We Offer:

• Hands-on experience in one of the world’s most exciting emerging fields: brain-computer interfaces
• Opportunity to contribute to technology that directly improves lives
• Mentorship from scientists, engineers, and founders building real neurotechnology products
• Dynamic NYC workspace blending lab, workshop, and creative studio environments
• Potential for full-time conversion after graduation

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