Full time, Fixed Term: initially fixed for 24 months with the possibility for extension depending on funding and mutual agreement.
A postdoctoral Research Fellow position is open in the Data-Driven Materials Discovery & Materials Informatics Group of Prof Adham Hashibon at UCL. Outstanding highly motivated candidates are sought with strong background in materials modelling and computational physics/chemistry. Candidates are expected to participate and contribute to exciting developments in emerging integrated materials modelling approaches spanning various models and scales (from electronic, atomistic to mesoscopic and continuum). The focus is to create a framework for validation of advanced materials models with use of artificial intelligence (AI) including of course machine learning (ML) approaches. In addition, ample opportunities will be provided to engage in the emerging fields of Materials Informatics and Materials Data Science, including Machine Learning innovative applications, knowledge graphs, ontology and e-science open digitalization frameworks.
Depending on the skill set and interest of the candidate either a track focused on the application of materials models, or a track for the development of such methodologies are possible. Knowledge of computational modelling of materials in general, and specifically of Density functional Theory (DFT) or Molecular Dynamics (MD) is required. Expertise in continuum modelling of mechanical properties or fluids is desired but not required. Ample networking and collaboration opportunities within UCL within the Chemistry, Physics and Engineering departments as well as with the emerging UCL East campus in London and with leading international researchers and industry are offered.
The position is supported primarily by the European Commission’s Horizon 2020 grant OpenModel (https://open-model.eu) and is initially fixed for 24 months with the possibility for extension depending on funding and mutual agreement.
PhD or equivalent work experience in computational physics, chemistry or materials science, or equivalent engineering related topics (including computer science or data science). Demonstrable experience in either electronic first principles Density Functional Theory (DFT) methods or atomistic molecular dynamics (MD) or similar. The successful candidate must have a keen interest developing and understanding the interplay between data-based and physics-based models.
Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, the initial appointment will be at Research Assistant Grade 6B(salary £32,217 – £33,958 per annum including London Allowance) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.
Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button above.
For informal enquiries about the role, please contact Prof. Adham Hashibon ([email protected]).
Please send any queries regarding the vacancy or the application process to Mr Alex Balciunas, [email protected].
Latest time for the submission of applications: 23:59.
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