Difference between revisions of "Vacancies"

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=== General Purpose Machine Learning Tool-Kit for Bragg Coherent Diffraction Imaging ===
 
=== General Purpose Machine Learning Tool-Kit for Bragg Coherent Diffraction Imaging ===
  
Deep learning has has emerged as a powerful alternative to the iterative phase retrieval approach, that can provide robust reconstruction of Fourier-space diffraction pattern data where iterative methods often fail to solve the phase retrieval problem. Although emphasis to date has focussed on inversion from Fourier-space to real-space images, the process of recovering real-space images remains unclear due to the inherent and currently intractable complexity of deep learning methods. In this project you will develop Physics-Aware Super-Resolution convolutional neural network tools to enhance the visibility of Fourier-space diffraction patterns thus enabling rapid and accurate reconstruction of phase information. This project is a collaboration between the Ada Lovelace Institute, the Diamond Light Source and the University of Southampton.
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Deep learning has has emerged as a powerful alternative to the iterative phase retrieval approach, that can provide robust reconstruction of Fourier-space diffraction pattern data where iterative methods often fail to solve the phase retrieval problem. Although emphasis to date has focussed on inversion from Fourier-space to real-space images, the process of recovering real-space images remains unclear due to the inherent and currently intractable complexity of deep learning methods. In this project you will develop Physics-Aware Super-Resolution convolutional neural network tools to enhance the visibility of Fourier-space diffraction patterns thus enabling rapid and accurate reconstruction of phase information. This project is a collaboration between the [https://adalovelacecentre.ac.uk/ Ada Lovelace Centre], the [https://www.diamond.ac.uk Diamond Light Source] and the University of Southampton.
  
 
Applications are invited online [https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page here]. When completing the online form, Select "Programme type: Research", "Academic Year: 2024/25", "Faculty: Faculty of Physical Sciences and Engineering".  Then select the "PhD Physics (Full time)" course title. Once logged on, in the supervisor name field, insert "Marcus Newton".
 
Applications are invited online [https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page here]. When completing the online form, Select "Programme type: Research", "Academic Year: 2024/25", "Faculty: Faculty of Physical Sciences and Engineering".  Then select the "PhD Physics (Full time)" course title. Once logged on, in the supervisor name field, insert "Marcus Newton".
 
  
 
=== Imaging Quantum Materials with an XFEL ===
 
=== Imaging Quantum Materials with an XFEL ===

Revision as of 09:55, 11 March 2024



Vacancies:

General Purpose Machine Learning Tool-Kit for Bragg Coherent Diffraction Imaging

Deep learning has has emerged as a powerful alternative to the iterative phase retrieval approach, that can provide robust reconstruction of Fourier-space diffraction pattern data where iterative methods often fail to solve the phase retrieval problem. Although emphasis to date has focussed on inversion from Fourier-space to real-space images, the process of recovering real-space images remains unclear due to the inherent and currently intractable complexity of deep learning methods. In this project you will develop Physics-Aware Super-Resolution convolutional neural network tools to enhance the visibility of Fourier-space diffraction patterns thus enabling rapid and accurate reconstruction of phase information. This project is a collaboration between the Ada Lovelace Centre, the Diamond Light Source and the University of Southampton.

Applications are invited online here. When completing the online form, Select "Programme type: Research", "Academic Year: 2024/25", "Faculty: Faculty of Physical Sciences and Engineering". Then select the "PhD Physics (Full time)" course title. Once logged on, in the supervisor name field, insert "Marcus Newton".

Imaging Quantum Materials with an XFEL

Quantum materials can often exhibit novel and multifunctional properties due to strong coupling between lattice, charge, spin and orbital degrees of freedom. When perturbed into an excited state, non-equilibrium phases often emerge on the femtosecond timescale. They include light-induced superconductivity, terahertz-induced ferroelectricity and ultra-fast solid-phase structural transformations. Understanding non-equilibrium phases in quantum materials is of great interest for the development of next generation technologies and to better understand the underlying mechanisms. To further understand these hidden phases, tools to probe quantum materials with femto-second time-resolution are required.

X-ray Free Electron Laser (XFEL) facilities provide ultra-short pulses of coherent x-rays that make it possible to measure ultra-fast dynamics in quantum materials simultaneously with nanoscale spatial resolution and femto-second time resolution. While preliminary work has begun on the use of XFELs to study quantum behaviour in materials, there are a wide range of strongly correlated materials that exhibit novel behaviour that is not well understood.

This project will investigate strongly correlated phenomena in nanoscale quantum materials using time-resolved Bragg coherent diffraction imaging (CDI) at various XFEL facilities. Initial emphasis will reside on the study of structural phase changes in strongly correlated quantum materials such as vanadium dioxide but will continue to expand to other material systems throughout the duration of the project. The overarching goal is to directly observe atomic motions during the event of a quantum phase transition. The ability to quantitatively observe atomic motions within the transition state region where atoms exchange nuclear configurations will greatly facilitate our understanding of the physical processes.

This project is fully funded for 3.5 years, supervised by Dr Marcus Newton and will benefit from access to the European XFEL, Swiss XFEL, SACLA XFEL and PAL XFEL. A background in physics, materials science or inorganic chemistry is desirable but not essential.

Applications are invited online here. When completing the online form, Select "Programme type: Research", "Academic Year: 2024/25", "Faculty: Faculty of Physical Sciences and Engineering". Then select the "PhD Physics (Full time)" course title. Once logged on, in the supervisor name field, insert "Marcus Newton".