Difference between revisions of "Vacancies"
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| + | <metadesc>Research vacancies in the Coherent X-ray Science Group. Please discuss further with Marcus Newton. </metadesc> | ||
== Vacancies: == | == Vacancies: == | ||
| − | === | + | <!-- |
| + | === Research Fellow in Coherent Diffraction Imaging === | ||
| − | + | This exciting research post is part of the recently funded UKRI FLF project in the area of x-ray imaging of quantum materials. The aim is to utilise coherent diffraction imaging (CDI) techniques to study quantum phenomena in a range of multifunctional materials using our newly completed state-of-the-art in-house x-ray imaging facility and various synchrotron x-ray facilities. We have designed a novel pulsed laser deposition (PLD) system to automate the design and fabrication of nanoscale materials that permits rapid preparation and optimisation. Our current focus is on perovskite materials for energy efficient technologies and lithium-ion batteries. | |
| − | + | You will utilise our facilities to synthesis and characterise materials for synchrotron experiments. We have developed cutting edge tools that include machine learning methods for analysis of data from synchrotron experiments. You will work as a team and jointly with our collaborators to prepare samples, attend synchrotron experiments and analyse the resulting data. Field work will initially take place at the Diamond Light Source in Oxford. | |
| − | To | + | To be successful you will have a PhD* or equivalent professional qualifications and experience in one of the following Physics; Materials Science; Optoelectronics; Engineering or a related field along with knowledge of coherent x-ray diffraction imaging or related techniques. In addition, you will have experience of coherent x-ray diffraction imaging or related techniques and a good understanding of a scientific computing language such as Python. |
| + | This post is offered on a full-time, fixed term basis for 2 years due to funding requirements, with a possible extension to 4 years. | ||
| − | = | + | Apply now [https://jobs.soton.ac.uk/Vacancy.aspx?ref=1869622WF here]. |
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| − | + | <!-- | |
| + | === Imaging Multifunctional Nanomaterials in Three-Dimensions with Coherent X-rays === | ||
| − | + | Multifunctional materials that simultaneously exhibit more than one ferroic property including ferromagnetism, ferroelectricity, ferroelasticity or ferrotoroidicity are of great interest because the different properties may work together in different ways and lead to exciting new potential applications, if we could understand this better. For example, the coupling between magnetic and ferroelectric ordering can be utilised to develop low power magnetoelectronic devices (such as non- volatile magnetic computer memory) where the spin polarised transport of electrons can be used to flip magnetic memory bits. As a result there is a vibrant effort to understand the underlying mechanisms at work in bulk and thin film materials. Often the role of crystal defects and other topological structures remains unclear as (to date) no reliable means exists to image in three-dimensions and observe such effects in real-time. | |
| + | In addition, common Li-ion battery cathode materials such as Li<sub>x</sub>CoO<sub>2</sub> (LCO) allow high capacities and reliable cyclability, but suffer from structural degradation over repeated charging cycles. | ||
| − | + | The aim of this project is to image time-varying correlated phenomena in a range of multifunctional materials. The results will (1) facilitate in identifying new and potentially novel applications for the materials of interest, (2) provide insight into scale-invariant properties of correlated material systems and (3) provide improved performance of battery materials. | |
| − | The | + | To better understand these materials we will use a technique called Bragg coherent X-ray diffractive imaging (BCXDI) without lenses to reveal how novel phases emerge and influence the material properties. The application of BCXDI to the study of multifunctional materials will enable a wide range of next generation technologies that otherwise are inaccessible due to an incomplete understanding of their properties. The successful candidate will spend approximately 50% of their time on the project working at the Diamond Light Source, located at the Harwell Science and Innovation Campus in Oxfordshire. |
| − | Applications are invited from bright and highly motivated students with a background in physics, materials science, inorganic chemistry or a related field. | + | Applications are invited from bright and highly motivated students with a background in physics, materials science, inorganic chemistry or a related field. The successful candidates will have obtained either a First or Upper Second class honours degree. |
| − | + | --> | |
| + | === General Purpose Machine Learning Tool-Kit for Bragg Coherent Diffraction Imaging === | ||
| − | |||
| − | + | Bragg coherent diffraction imaging (BCDI) is a lens-less far field x-ray imaging technique that allows three-dimensional (3D) imaging of quantum materials at the nanometre scale with a sensitivity below a single angstrom. To accomplish this, coherent x-rays from a synchrotron light source are used to illuminate a single nanocrystal which scatters to produce a diffraction (speckle) pattern. That pattern encodes all information about the arrangement of atoms within the nanocrystal. Iterative phase reconstruction computational methods are then routinely used to recover the complex three-dimensional electron density and phase information, which is related to strain in the nanocrystal. | |
| + | |||
| + | Deep learning 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. You will build on our recent and significant developments in machine learning (ML) for phase retrieval. You will then apply the newly developed ML tools to study quantum materials at the nanoscale using BCDI. Quantum materials of interest include multiferroics for next generation neuromorphic computing and Li/Na-ion battery cathode materials. | ||
| − | + | This project is a collaboration with the Ada Lovelace Institute and Diamond Light Source. | |
| − | + | Applications are invited online [https://www.southampton.ac.uk/study/postgraduate-research/apply here]. When completing the online form, Select "Programme type: Research", "Academic Year: 2024/25", "Faculty: Faculty of Engineering and Physical Sciences". Then select the "PhD Physics (Full time)" course title. | |
| + | |||
| + | === 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 [https://www.southampton.ac.uk/study/postgraduate-research/apply here]. When completing the online form, Select "Programme type: Research", "Academic Year: 2024/25", "Faculty: Faculty of Engineering and Physical Sciences". Then select the "PhD Physics (Full time)" course title. | ||
Latest revision as of 09:33, 15 October 2024
Vacancies:
General Purpose Machine Learning Tool-Kit for Bragg Coherent Diffraction Imaging
Bragg coherent diffraction imaging (BCDI) is a lens-less far field x-ray imaging technique that allows three-dimensional (3D) imaging of quantum materials at the nanometre scale with a sensitivity below a single angstrom. To accomplish this, coherent x-rays from a synchrotron light source are used to illuminate a single nanocrystal which scatters to produce a diffraction (speckle) pattern. That pattern encodes all information about the arrangement of atoms within the nanocrystal. Iterative phase reconstruction computational methods are then routinely used to recover the complex three-dimensional electron density and phase information, which is related to strain in the nanocrystal.
Deep learning 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. You will build on our recent and significant developments in machine learning (ML) for phase retrieval. You will then apply the newly developed ML tools to study quantum materials at the nanoscale using BCDI. Quantum materials of interest include multiferroics for next generation neuromorphic computing and Li/Na-ion battery cathode materials.
This project is a collaboration with the Ada Lovelace Institute and Diamond Light Source.
Applications are invited online here. When completing the online form, Select "Programme type: Research", "Academic Year: 2024/25", "Faculty: Faculty of Engineering and Physical Sciences". Then select the "PhD Physics (Full time)" course title.
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 Engineering and Physical Sciences". Then select the "PhD Physics (Full time)" course title.