quantum machine learning

Ph.D. POSITION
We are looking for two talented and highly skilled students to work toward their PhD degree on signal processing of quantum-enhanced sensors and validate the same with experimental data in the Classical and Quantum Signal Processing (CAQ-SP) Group at Carleton University led by Prof. Sreeraman Rajan.
The research will be focused on:
• Quantum-enhanced radar and lidar performance prediction
• Signal processing for quantum sensors
• Classical and quantum machine learning for detection and identification

The Department of Mathematics of the University of Bologna has an opening for a 2-year postdoc in Mathematical Physics on the PRIN project “Understanding the learning process of quantum neural networks” coordinated by Giacomo De Palma (University of Bologna, Mathematics Department) together with Leonardo Banchi (University of Florence, Physics Department) and Dario Trevisan (University of Pisa, Mathematics Department):
https://bandi.unibo.it/ricerca/assegni-ricerca?id_bando=67126

The nanoelectronics theory groups at Forschungszentrum Juelich and RWTH Aachen are looking for highly motivated candidates to fill a Ph.D. position. The position can start immediately. The PhD candidate will conduct research on theoretical aspects of quantum machine learning and circuit QED.

The Department of Physics of the Polytechnic University of Bari (Italy) is offering a fellowship in quantum information theory, for computing, metrology, and communications.

We welcome applications from candidates interested in any theoretical aspect of quantum information science and technology. Some knowledge of Italian is expected.

Deadline is February 27th, 2023.

Have you ever wanted to take part in the development of top photonic quantum technologies which will change our future? Are you eager to work side by side and learn from with the best quantum scientists, space agencies and high-tech companies? Do you want to boost your career in academia or business R&D in Europe and beyond? If your answer is “yes”, you are highly creative and hold a PhD in physics, computer science or mathematics or you will graduate in the next few months, then join our multi-national Quantum Technologies Research Group led by Prof. Magdalena Stobińska at the University of Warsaw. We have now 3 open positions which we plan to fill as soon as possible.

Have you ever wanted to take part in the development of top photonic quantum technologies which will change our future? Are you eager to work side by side and learn from with the best quantum scientists, space agencies and high-tech companies? Do you want to boost your career in academia or business R&D in Europe and beyond? If your answer is “yes”, you are highly creative and hold a PhD in physics, computer science or mathematics or you will graduate in the next few months, then join our multi-national Quantum Technologies Research Group led by Prof. Magdalena Stobińska at the University of Warsaw. We have now 3 open positions which we plan to fill as soon as possible.

Have you ever wanted to take part in the development of top photonic quantum technologies which will change our future? Are you eager to work side by side and learn from with the best quantum scientists, space agencies and high-tech companies? Do you want to boost your career in academia or business R&D in Europe and beyond? If your answer is “yes”, you are highly creative and hold a PhD in physics, computer science or mathematics or you will graduate in the next few months, then join our multi-national Quantum Technologies Research Group led by Prof. Magdalena Stobińska at the University of Warsaw. We have now 3 open positions which we plan to fill as soon as possible.

Quantum- and physics-inspired optimization has attracted lots of attention in recent years, as fundamentally novel paradigms towards solving large-scale combinatorial problems. The underlying principle is to encode a given problem into the natural dynamics of physical systems, and to achieve potentially stronger convergence and higher precision through careful external control. Physics-inspired optimization algorithms, such as coherent Ising machines and simulated bifurcation, mimic the dynamical properties of physical systems on conventional hardware – with the goal to inherit certain features, such as natural convergence towards low-energetic states. At Huawei, we investigate a wide range of topics related to quantum- and physics-inspired optimization, from the most fundamental mathematical structures, deep understanding of physical models, to high-performance implementation of novel optimization architectures.

We are looking for a highly motivated Ph.D. student to work in the following fields:

- Quantum neural networks.

- Developing new quantum machine learning protocols. Problems o interest include quantum state preparation, quantum feature detection, or developing hybrid quantum architectures."

- Resource theory of quantum machine learning.