2026 PEER-REVIEWED COHORT
A global, research-driven cohort exploring computational neuroscience, brain-inspired AI, and the science of human-machine cognitive integration.
Duration
12 Weeks
Start Date
July 6, 2026
The HyperQuark Research Fellowship (HQ-Su26) is a 12-week research-driven program operating under the Center for Computational NeuroIntelligence & Cognitive AI Systems (CCNI) - bringing together globally distributed researchers, engineers, and thinkers to work on advanced problems at the intersection of artificial intelligence and human neuroscience.
The fellowship operates as a research lab environment where participants engage with neural signal data, brain-inspired computational architectures, cognitive augmentation systems, and neurotechnology governance - producing original research outputs at a standard aligned with leading institutions including IRCN Tokyo, RIKEN Center for Brain Science, Max Planck MPI-CBS, Stanford Neurosciences Institute, UCL Queen Square, and CCBR IIT Madras.
The program bridges theoretical neuroscience and applied AI research, with a direct connection to HyperQuark’s broader mission of career intelligence and human-centered intelligent systems.
The primary objective of the fellowship is to produce meaningful research contributions that advance the understanding and application of neural-AI integration across scientific, systems, and governance dimensions.
Participants are expected to:
• Engage with primary literature and open neuroimaging and biosignal datasets
• Develop falsifiable research claims grounded in empirical or formal evidence
• Collaborate across neuroscience, AI, cognitive science, and policy disciplines
• Contribute to research papers, computational models, and technical frameworks
• Build clarity in experimental thinking, scientific communication, and systems design
1) Computational Neural Signal Modeling
Focuses on processing and decoding neural signals — EEG, fMRI, MEG — using machine learning pipelines to classify cognitive states, model brain activity, and advance brain-computer interface research.
2) Neuromorphic AI Architecture
Investigates AI systems designed around the computational principles of the biological brain — spiking neural networks, spike-timing-dependent plasticity, and energy-efficient architectures inspired by cortical structure.
3) Human-AI Cognitive Augmentation
Develops adaptive AI systems that model individual cognitive styles, skill acquisition patterns, and learning trajectories — with direct application to personalized career intelligence and human capability development.
4) Neurorights, Ethics & AI Governance
Examines the policy, consent, and governance challenges arising from neurotechnology-adjacent AI — including neural data privacy, cognitive liberty, and frameworks for responsible deployment of brain-computer interface systems.
The fellowship follows a structured research model over 12 weeks.
Each week includes:
• A common cohort session across all tracks
• Track-specific collaboration and experimentation
• Independent research, literature engagement, and artifact development
• Weekly progress reporting and milestone documentation
Participants work both synchronously and asynchronously, supported by collaborative tools. A mid-program research showcase at Week 6 and a final symposium at Week 12 anchor the cohort calendar.
Throughout the fellowship, participants contribute to:
• Research problem statements with falsifiable claims
• Annotated literature reviews and comparative analyses
• Computational models, signal processing pipelines, and prototype systems
• Evaluation frameworks and benchmark results
• Research papers, technical reports, and policy briefs
Selected work may be developed into arXiv preprints, peer-reviewed publications, or integrated into HyperQuark’s broader research ecosystem.
The HQ-Su26 cohort consists of participants from multiple countries, spanning research backgrounds in neuroscience, artificial intelligence, cognitive science, computational biology, and AI policy.
The distributed nature of the cohort enables diverse methodological perspectives, interdisciplinary collaboration, and exposure to global approaches in both brain science and AI research.
The fellowship operates on a co-ownership model where participants actively contribute to shared research outcomes.
Work developed during the fellowship is collaboratively created and attributed, with contributions recognized across all research outputs.
HyperQuark Intelligence Labs may utilize research outcomes for further development, publication, and integration into its broader intelligence systems ecosystem.
The fellowship selects individuals based on intellectual curiosity, scientific rigor, research intent, and alignment with the mission of advancing the science of intelligence — both biological and artificial.
The focus is not only on prior experience, but on the capacity to engage deeply with complex problems, collaborate across disciplines, and contribute to research directions that sit at the frontier of neuroscience and AI.
Backgrounds in neuroscience, ML/AI, cognitive science, computational biology, and AI policy are all relevant. Interdisciplinary profiles are strongly encouraged.
Applications and further details coming soon. Follow HyperQuark Intelligence Labs for updates.