Energy-Efficient Storage Technologies and Quantum Materials

Summary:

Applications are invited for a 4-year PhD studentship within the new established EPSRC funded Centre for Doctoral Training in Sensing, Processing, and AI for Defence and Security (SPADS). The program involves both a PhD research project and integrated studies as part of a cohort of like-minded students. The integrated studies will include advanced courses and bespoke training events such as summer schools, specialised theme meetings, and innovation and commercialisation sandpits.

Description:

With the advent of 5G networks, Internet of Things (IoT), particularly in the defence and security area, there is an exponential growth on the amount of data generated worldwide. It is estimated that by 2025, more than 175 Zettabyte (1 Zettabyte=10⁹ Terabytes) of data per year will be produced. Indeed, information technology is predicted to consume 21% of the world electricity supply by 2030. There is hence a pressing economic and societal urge to find more energy efficient solutions. To make progress in the targeted area of quantum storage technologies, new materials and/or processes need to be created or found. Therefore, the proposed project aims to: (i) find the most promising compounds displaying magnetic textures at technologically relevant temperatures, (ii) understand the quantum interactions between electrical currents, femtosecond laser pulses with spin-lattices, (iii) design energy-saving and high-performance quantum computing mechanism for applications in quantum storage technologies (QSTs).

Objectives:

• To design new quantum magnetic devices where energy-efficient operations are developed with optimized computing architectures beyond classical approaches,

• To model and improve scalability and intrinsically integrate AI self-learning capabilities within the material at large-scale production, and

• To target high density at low-power consumption for multifunctional device-platforms for quantum storage technologies (QSTs)

Eligibility

The position is open for candidates interested in performing either experiments and lab focused-work, or simulations and theory. The decision on what focus (measurements or theory) the PhD thesis would be it will be based on the skills of the successful candidate. Thus, some previous experience in any of the following is a plus:

• Monte Carlo and micromagnetic techniques
• Open-source ab initio codes (e.g., KKR, VASP, Quantum-Espresso, etc.).
• Coding languages (e.g., C/C++, Python, Matlab, etc.)
• Nanofabrication technologies (e.g. lithography, etching, atomic layer deposition)
• Magnetic techniques and optical characterisation

On the theory side, the candidate will develop several computational skills in terms of first-principles methods (e.g., strongly correlated systems), Monte Carlo, Landau-Lifshitz-Gilbert equation techniques, and data-driven approaches (e.g., deep-learning). Both method development and utilisation of in-house codes will be undertaken during the project. 

On the experimental side, the candidate will have access to the Scottish Microelectronics Centre for the fabrication of the designed materials and devices. Training on nanofabrication, measurement technologies and clean-room skills will be undertaken.  

The successful candidate will work closely with other PhDs and postdocs involved in similar investigations.    

Experimental and theoretical collaborations: The project will be developed in collaboration with several world-class groups (experimental, theory) at the National University of Singapore, Max Planck Institute, Argonne National Laboratory, Northwestern University.

Students are expected to hold a 2.1 Hons degree or above, or equivalent, in Electronics and Electrical Engineering, Computer Science, Physics or related discipline. A Master’s degree in one of the above fields would be advantageous.

Applicants who require an ATAS certificate to work study in the UK will not be eligible for this PhD programme. A list of nationalities that do not require ATAS certification can be found here – https://www.gov.uk/guidance/find-out-if-you-require-an-atas-certificate

Further information on English Language requirements: https://www.ed.ac.uk/studying/postgraduate/applying/your-application/entry-requirements

Further Information

PhD Project to be run through the Centre for Doctoral Training in Sensing, Processing, and AI for Defence and Security (SPADS). For more information, please visit: https://spads.ac.uk/

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here:https://www.ed.ac.uk/equality-diversity

Informal queries should be directed to Prof Rebecca Cheung (R.Cheung@ed.ac.uk), and Dr Elton Santos (esantos@ed.ac.uk.