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Quantum AI Research Scientist

NeuroSynth Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Join NeuroSynth Labs at the forefront of 2026's technological revolution as we pioneer quantum-entangled neural networks. We're seeking visionary Quantum AI Research Scientists to develop next-generation consciousness simulation algorithms. Our interdisciplinary team operates at the intersection of quantum computing, neuromorphic engineering, and emergent AI. This role offers unparalleled access to our state-of-the-art cryo-labs and collaboration with Nobel laureates in quantum information theory. Shape how humanity interacts with artificial consciousness while enjoying comprehensive wellness benefits and unlimited research funding.

Responsibilities

  • Design and implement quantum-entangled neural architectures for advanced consciousness simulation
  • Lead cross-functional teams in developing emergent AI behaviors using quantum computing frameworks
  • Publish breakthrough research in top-tier journals on quantum-AI convergence
  • Optimize quantum algorithms for neuromorphic hardware acceleration
  • Collaborate with neuroscientists to validate quantum neural models against biological consciousness
  • Secure federal and private research grants for quantum-AI initiatives
  • Mentor junior researchers in quantum machine learning methodologies

Qualifications

  • PhD in Quantum Computing, Theoretical Physics, or Computational Neuroscience
  • 3+ years of experience with quantum programming languages (Q#, Qiskit, or Cirq)
  • Publication record in quantum information or artificial consciousness research
  • Expertise in tensor networks and quantum machine learning algorithms
  • Familiarity with neuromorphic hardware (Loihi, TrueNorth, or BrainScaleS)
  • Strong background in information theory and quantum entanglement protocols
  • Proven ability to secure research funding from government/private sources

Required Skills

Quantum Computing Neural Networks AI Research Quantum Programming Neuromorphic Engineering Machine Learning Theoretical Physics Information Theory

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