TENORS (Tensor modEliNg, geOmetRy and optimiSation) is a Marie Skłodowska-Curie Doctoral Network / Joint Doctorate (2024-2027), offering
15 PhD positions
that are expected to start in September/October 2024.
The objective of TENORS is to conduct advanced research that addresses critical challenges in the fields of tensor modeling and computation, joining forces from algebraic geometry, global optimisation, numerical computation, high performance computing, data science, quantum physics.
PhD and PostDoc Positions Announcement
Cavity Electrodynamics for Quantum Cooperative Matter Control
The Chair of Solid State physics at the University of Erlangen is pleased to announce a fully positions in the cutting-edge research project, "Cavity Electrodynamics as a New Route To Control Quantum Cooperative Properties of Matter" (CENTQT).
Exciting PhD Opportunity in Cutting-Edge Quantum Research!
Are you ready to embark on a groundbreaking journey in quantum systems? An extraordinary PhD opportunity awaits, delving into uncharted territories at the intersection of applied and fundamental sciences. Join our dynamic team as we push the boundaries of knowledge and work towards developing a revolutionary radio-frequency signal detection scheme.
We are inviting applications for one open PhD position in theory of light-matter interaction at the Gonzalez-Ballestero group at the Vienna University of Technology, Austria.
Candidates must have a background in theoretical quantum physics with strong analytical skills. Our group is committed to contribute toward gender balance in Academia and thus female candidates are especially encouraged to apply.
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
Pages
