Job Description
Join Nexus Labs at the forefront of technological revolution as we pioneer the next wave of quantum-AI integration. We're seeking visionary Quantum AI Research Scientists to develop groundbreaking algorithms that will redefine computational boundaries. In this role, you'll collaborate with Nobel laureates and industry disruptors to build scalable quantum neural networks for real-world applications in cryptography, drug discovery, and climate modeling. Our Austin campus features state-of-the-art quantum labs, unlimited R&D resources, and a culture that celebrates intellectual audacity.
What you'll impact:
- Architect quantum machine learning frameworks capable of solving problems currently deemed unsolvable
- Lead cross-functional teams to translate theoretical quantum algorithms into production-ready systems
- Secure patents for breakthrough quantum-AI methodologies
- Present findings at premier conferences like Q2B and NeurIPS
Responsibilities
- Design and implement novel quantum algorithms leveraging Grover's search, Shor's factorization, and quantum Fourier transforms
- Develop hybrid quantum-classical neural networks with error mitigation protocols
- Collaborate with hardware teams to optimize algorithms for quantum processors
- Lead research initiatives in quantum machine learning and natural language processing
- Secure $5M+ in government and private research grants
- Mentor PhD researchers and publish 3+ high-impact papers annually
Qualifications
- PhD in Quantum Physics, Computer Science, or Computational Mathematics with 5+ years of quantum computing research
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and quantum circuit optimization
- Published work in Nature/Science journals or equivalent top-tier venues
- Proficiency in Python, TensorFlow/PyTorch, and high-performance computing frameworks
- Deep understanding of quantum error correction and fault-tolerant architectures
- Experience securing DoD or NSF grants
- Fluency in quantum machine learning and variational quantum algorithms