Job Description
Join Nexus Future Labs at the forefront of technological evolution as we pioneer quantum-AI integration for 2026's most critical challenges. We're seeking visionary researchers to architect hybrid quantum neural networks that will redefine machine learning. Our Austin campus features state-of-the-art quantum processors and collaborative innovation spaces where your work will directly impact breakthroughs in climate modeling, drug discovery, and autonomous systems.
This role offers unparalleled resources including access to IBM Quantum and AWS Braket platforms, with opportunities to publish in Nature and present at IEEE Quantum Week. You'll collaborate with Nobel laureates and lead projects funded by the National Science Foundation's 2026 Quantum Leap Initiative.
Responsibilities
- Design and implement novel quantum algorithms for AI optimization problems
- Develop hybrid quantum-classical machine learning frameworks
- Lead experimental validation on superconducting quantum processors
- Author peer-reviewed publications and technical white papers
- Secure NSF/DARPA grants for quantum-AI research initiatives
- Mentor PhD candidates in quantum information science
- Collaborate with hardware engineers to co-design quantum processors
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
- 3+ years experience with quantum circuit simulation frameworks (Qiskit, Cirq)
- Publication record in Nature/Science or IEEE Transactions on Quantum Engineering
- Expertise in Python, TensorFlow, and quantum machine learning libraries
- Deep understanding of quantum error correction and fault tolerance
- Experience with superconducting or trapped-ion quantum systems
- Demonstrated ability to secure federal research grants