Research Assistant in Data Storage Applications using Two-Dimensional Materials
Job reference 18/106594
Application closing date 14/08/2018
Salary £27,285 - £31,604 per annum (potential to progress to £34,520 per annum through sustained exceptional contribution)
Job category/type Research
Applications are invited for a 9-month Postdoc fellowship based at Queen's University Belfast, to work in the area of First-Principles Methods for the Next Generation of Data Storage Applications using Two-Dimensional Materials.
The Postdoc Research Fellowship is part of the US-Ireland R&D Partnership Programme recently funded by the NSF (USA), SFI (Republic or Ireland) and DELNI (North Ireland). The partnership involves the groups led by Prof. Manish Chhowalla at Rutgers University in New Jersey (USA), Prof. Valeria Nicholosi at Trinity College Dublin (Republic of Ireland), and Dr. Elton Santos at the Atomistic Simulation Center at Queen's University Belfast, United Kingdom.
The research focus will be on simulations and method development using advanced first-principles approaches on the spin-properties of a variety of 2D-materials, such as transition metal dichalcogenides, and their van der Waals heterostructures. The theory will guide, complement and support the experimental work performed at Chhowalla's and Nicolosi's groups which will be devoted to synthesis, characterization and device-performance evaluation using the state-of-the-art experimental techniques at world class facilities. Several trips and research visits to both labs will be a crucial part of the project.
Access to supercomputer facilities at Queen's University, UK National Supercomputing Service (ARCHER), University College London (UCL) will be available during this project.
We are looking for a motivated candidate with a solid background in condensed matter physics, interested in computational methods, materials informatics, good command of written and spoken English. A previous background in electronic structure methods (DFT, Hartree-Fock, magnetism, electronic transport) would be fundamental. Knowledge of coding languages such as Fortran, C/C++, Python or Awk is essential. Experience on modern open source software's such as Vasp, Castep, Quantum Espresso is required.
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