Quantum Algorithm Engineer, Quantum Machine Learning (m/w/d)
München, Germany
IQM Quantum Computers
IQM is a global leader in designing, building, and selling superconducting quantum computers. IQM provides both on-premises full-stack quantum computers and a cloud platform to access its computers anywhere in the world. IQM customers include the leading high-performance computing centres, research labs, universities and enterprises which have full access to IQM's software and hardware. IQM has over 280 employees with offices in Finland, Germany, France, Spain, Poland, Singapore and the US.
We are looking for an expert in Quantum Machine Learning to join our team to help develop promising and rigorously justified quantum algorithms, with a focus on the NISQ and early fault tolerant era. You will be embedded in the Algorithm and Application Team actively exploring and optimising quantum algorithms, as well having the opportunity to work with other technical R&D teams at the frontier of all aspects of the quantum computing stack.
This position offers you the chance to meaningly influence the direction of quantum computing, in an open and flexible environment and with liberal access to cutting edge quantum hardware. Candidates are preferred for IQM's Munich location, but we are open to consider other IQM locations for the strong candidates.
What will I be doing?
- You will be developing new and improving existing quantum machine learning algorithms, to apply to existing problems or to showcase available speed-ups.
- You will be analysing the performance of these algorithms in terms of scaling complexity and noise robustness.
- You will be implementing quantum algorithms on IQM quantum hardware.
- You will be publishing high impact research at the frontier of quantum science.
What skills do I need?
Required skills
- PhD in theoretical physics, computer science, mathematics or similar field, or equivalent company experience.
- Deep knowledge of quantum machine learning and quantum information theory.
- Advanced knowledge of classical algorithms for machine learning; e.g. Kernel-based methods, Boltzmann machines, transformer architectures, generative adversarial networks, general deep neural network methods.
- Solid experience in at least one of the following areas:
- Theoretical analysis of quantum machine learning algorithmic performance.
- Computational complexity analysis of quantum tasks e.g. sampling.
- Analysis of algorithmic performance under presence of noise.
- Quantum generative learning.
- 2+ years of experience in developing code for scientific applications.
Nice-to-have skills
- Practical experience in problem solving via classical machine learning.
- Experience in running quantum algorithms on quantum hardware.
- Experience in post-processing techniques e.g. classical shadows.
Soft skills
- You feel comfortable in a team-oriented collaborative environment.
- You keep your skills and knowledge fresh and are always eager to learn more.
- You create elegant solutions amidst complexity.
- You care deeply about building quality and keeping the internal and external quality of your code high.
- You understand how to balance current needs with future capability and extensibility.
What I can expect from IQM?
- An excellent opportunity to collaborate on world-class R&D and cutting-edge technology.
- An opportunity to work with a passionate and diverse company on a critical mission.
- A unique opportunity to make a real impact on the future of quantum.
- Growth and progress in a creative and open start-up environment.
- Team with a relaxed and cozy atmosphere.
Meet our people and hear more about IQM by visiting our Youtube channel here >>
We'll proceed with the interviews immediately, so please submit your application soon.
Please note that only applications submitted through the website will be processed.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Computer Science GANs Machine Learning Mathematics PhD Physics Quantum algorithms R R&D Research
Perks/benefits: Career development Startup environment
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