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PhD candidate in computational catalysis researc ... (No replies)
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We seek a candidate with a strong theoretical background in condensed matter physics / physical chemistry as well as expertise in electronic structure calculations and programming. The candidate should contribute actively to the computational catalysis projects at NTNU by carrying out DFT simulations of electrochemical reactions and participating in method development. The project objectives are threefold: (i) Better understanding of basic electrochemical reactions relevant for renewable energies and carbon recycling (fundamental science), (ii) contributing in materials design for better catalyst materials – in particular in terms of replacing critical metals (sustainability), and (iii) methodology development to extend the existing materials modelling platform (software, algorithms, workflows) towards more complicated (electro)chemical reactions (progress beyond the previous H2020 project, http://www.critcat.eu).
The position considers electrochemical simulations at the DFT level by using existing software packages and material modelling platform, and focuses on the following aspects:
Method development / testing will be carried out for high-throughput adsorption mapping of reactants on catalyst nanoparticle surfaces under alkaline conditions. Based on the collected data, the candidate will participate in the development of machine learning algorithms for descriptor-based materials screening of improved catalyst materials.
PhD candidates are normally remunerated at gross from NOK 482 200 per annum before tax, depending on qualifications and seniority. The period of employment is 4 years (with 25% teaching responsibility).
If you have any questions about the position, please contact Prof. Jaakko Akola, email [email protected]. Applications submitted via email will not be considered, please use the application portal instead.
See more and how to apply:
https://www.jobbnorge.no/en/available-jobs/job/203255/phd-candidate-in-computational-catalysis-research