Job Description
Join Nexus Labs at the forefront of technological evolution for our groundbreaking 2026 Visionary Program. We're seeking pioneering AI Research Scientists to architect the next generation of intelligent systems. As a key member of our Future Intelligence Division, you'll collaborate with Nobel laureates and industry disruptors to develop quantum-resistant AI models, ethical neural networks, and autonomous cognitive frameworks. Our state-of-the-art lab features exascale computing resources and neuro-quantum interfaces, enabling unprecedented breakthroughs in machine consciousness and predictive analytics.
This role offers unparalleled opportunities to publish in Science and Nature, contribute to IEEE standards, and shape humanity's technological trajectory. Our compensation package includes equity in our AGI spinoff, comprehensive wellness programs, and flexible remote options with quarterly innovation retreats in Tokyo and Zurich.
Responsibilities
- Design and implement novel deep learning architectures for 2026-era computational challenges
- Lead cross-functional teams in developing ethical AI governance frameworks
- Author breakthrough research papers on quantum machine learning and neuromorphic computing
- Architect secure federated learning systems for global enterprise deployment
- Collaborate with neuroscientists to develop biologically-inspired AI models
- Mentor postdoctoral researchers in next-gen AI paradigms
- Present findings at premier conferences including NeurIPS, ICML, and FAccT
Qualifications
- PhD in Computer Science, Mathematics, or Computational Neuroscience with 3+ years postdoc experience
- Published record in top-tier AI/ML journals with h-index >25
- Expertise in transformer architectures, quantum algorithms, and differential privacy
- Proficiency in PyTorch 3.0, TensorFlow Quantum, and neuro-symbolic frameworks
- Demonstrated ability to secure $5M+ in government/private research grants
- Experience with neuromorphic hardware (Loihi, TrueNorth) and photonic computing
- Strong background in AI ethics, bias mitigation, and responsible innovation