Planckianis developing the core technology to power utility-scale quantum computers.
By design, our chip architecture decouples control lines from qubit count, removing a key bottleneck in scaling. It combines the proven reliability of superconducting circuits with a breakthrough approach to qubit control, paving the way for quantum computers capable of solving the world’s most challenging problems.
We are seeking aQuantum Scientist to join our Architectures team
What You'll be doing
- Contribute to the design and development of novel QPU architectures based on superconducting qubits, focusing on globally driven control schemes
- Model quantum system dynamics; develop gate-level and pulse-level models for entangling operations on QPUs
- Conduct dynamic simulations using QuTiP or equivalent frameworks
- Perform noise characterization and numerical analysis to predict device behavior and support experimental calibration and optimization
- Collaborate with the Hardware team pod to ensure simulation assumptions match physical device constraints and support QPU calibration methodology and Hamiltonian learning.
- Contribute to the development, maintenance, and improvement of Planckian's proprietary compilation platform.
Requirements
- PhD in Physics or related subject.
- Deep understanding of solid-state hardware platforms for quantum technologies (superconducting circuits, semiconductors).
- Advanced knowledge of quantum computation and quantum information.
- Programming skills, in particular Python
Every job has its challenges, and this one is no exception. While many companies gloss over them, we believe in being upfront:
- You’ll face tough situations, especially the classic challenge: people problems. Navigating human dynamics can be tricky and requires patience and empathy.
- Some work is unglamorous, but building a great company means rolling up your sleeves. From strategic decisions to hands-on grunt work, everyone contributes to the heavy lifting.
We're not looking for perfection; we're looking for people who are ready to grow through the hard parts and help us build something that lasts.
What We Offer
- Competitive salary + benefits
- Stock options
- Flexible working hours with hybrid working
- Ego-free, merit-based environment
Planckian is an equal-opportunity employer.
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The structural evolution of the quantum hardware sector necessitates a specialized class of researchers focused on the convergence of architectural design and system-level modeling. As the industry transitions from proof-of-concept experiments toward utility-scale roadmaps, the role of a Quantum Scientist serves as a critical bridge between fundamental physical principles and scalable device performance. This function addresses a major bottleneck in the systems engineering layer of the value chain, where the decoupling of control infrastructure from qubit density is paramount. Market signals indicate that the ability to model complex quantum dynamics is now a primary determinant for achieving high-fidelity operations in multi-qubit systems. By orchestrating the interplay between hardware constraints and numerical simulations, this role ensures that long-term technology trajectories remain grounded in realistic physical benchmarks.
The quantum computing industry is currently navigating a period of rapid technological maturation characterized by the emergence of "Early Fault-Tolerant" (EFT) architectures. Within this environment, the hardware domain represents the most capital-intensive segment of the ecosystem, where the successful scaling of superconducting circuits requires a transition from individual device tuning to automated, globally driven control schemes. This shift is essential to mitigate the "wiring bottleneck" that has historically limited the expansion of cryogenically cooled processors.
Macro-level analysis reveals that the sector is pivoting from pure academic research toward a system engineering discipline. This transition is driven by the need to synchronize internal development efforts with evolving software stacks and proprietary compilation platforms. Organizations are increasingly seeking experts who can translate abstract Hamiltonian dynamics into optimized gate-level and pulse-level models, ensuring that the physical layer can support the requirements of emerging fault-tolerant algorithms.
Furthermore, the integration of high-fidelity simulations into the hardware development lifecycle has become a strategic imperative for organizations aiming for utility-scale computation. This trend favors the use of open-source frameworks alongside proprietary toolchains to characterize noise sources and predict device behavior with high precision. As standardizing efforts continue, the industry focus is centering on the creation of reproducible calibration methodologies that can account for the environmental interactions and emergent disorder effects found in complex solid-state platforms.
The capability architecture for this role type centers on the synthesis of advanced quantum mechanics with numerical modeling and computational physics. At the foundational layer, mastery of solid-state hardware platforms is essential for ensuring that architectural designs remain fabrication-aware and physically viable. This technical proficiency is coupled with expertise in dynamic simulation environments, where QuTiP or similar frameworks are utilized to model entangling operations and system-level decoherence. These capabilities are critical for the structural throughput of hardware research, as they directly influence the stability of qubits and the fidelity of multi-component operations.
Beyond theoretical modeling, the role facilitates a high-level coupling between architectural innovation and experimental validation. This interface ensures that insights from noise characterization and numerical analysis are integrated back into the design of next-generation Quantum Processing Units. By establishing a robust feedback loop between simulation and physical device performance, these experts enable a level of operational readiness that allows for the implementation of error-correcting codes and sophisticated calibration workflows. This strategic alignment is vital for maintaining the integrity of the technology stack as hardware scales toward thousands of physical qubits.
Accelerates the deterministic progression of superconducting hardware toward utility-scale performance benchmarks
Mitigates systemic risks associated with control-line scaling by developing decoupled architectural frameworks
Facilitates the transition from proof-of-concept devices to manufacturable, high-density quantum processors
Reduces iteration friction between theoretical design and experimental calibration through high-fidelity modeling
Strengthens the long-term competitive positioning of hardware providers by securing expertise in novel QPU architectures
Harmonizes abstract quantum information theory with the practical constraints of solid-state device physics
Optimizes the lifecycle of quantum processors through the development of automated calibration and characterization protocols
Supports the scaling of quantum adoption by ensuring hardware reliability for complex fault-tolerant applications
Shortens the time-to-market for next-generation qubits by utilizing predictive numerical simulations
Improves the fidelity of entangling operations through the refinement of pulse-level control models
Protects capital-intensive R\&D investments by providing rigorous validation of architectural scaling strategies
Enables the strategic orchestration of hardware and software co-design to enhance overall system performance
Industry Tags: Quantum Hardware, Superconducting Qubits, QPU Architecture, Quantum Simulation, Noise Characterization, Pulse Engineering, Fault Tolerance, Systems Engineering
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