Sort by
Refine Your Search
-
computational materials science techniques (DFT, MD, machine learning force fields) with data-driven approaches. Design and implement high-throughput experimental workflows for thermal conductivity and phonon
-
research Job Requirements: PhD in Physics, Chemistry, Materials Science, or a closely related field Demonstrated expertise in DFT using packages such as VASP, Quantum ESPRESSO, or similar Experience in high
-
quantum chemistry (DFT) or theoretical spectroscopy are encouraged to apply. Two selected review papers: J. Vicha et al. Chem. Rev. 2020, 120, 7065, doi: 10.1021/acs.chemrev.9b00785 J. Novotny et al. Acc
-
include density functional theory (DFT) and higher level methods to accurately screen new systems based on their optoelectronic and vibrational properties. The role holder will develop and apply
-
include density functional theory (DFT) and higher level methods to accurately screen new systems based on their optoelectronic and vibrational properties. The role holder will develop and apply
-
computational materials science techniques (DFT, MD, machine learning force field modelling) with data-driven approaches. Work with team to design and implement high-throughput experimental workflows for rapid
-
to principal investigator Assist in proposal preparation Job Requirements: PhD in chemistry, physics, chemical engineering, computer science, or other related fields Research background in theoretical catalysis
-
frameworks (MOFs), and related materials using hybrid classical-quantum algorithms. A key component of the role involves using first-principles methods that capture strong electronic correlations, such as DFT
-
of yourself or others. About the successful applicant (Selection Criteria) To be successful in this role you will have: A PhD in Chemistry, Chemical Engineering or Materials Science. Demonstrated prior research
-
to the effective supervision of Honours and Higher Degree by Research (e.g., PhD, Masters) students (as appropriate). Demonstrate personal effectiveness in supervision and the management of researcher development