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Computational modelling of bionano interface

Project Description

EU H2020/SFI funded Postdoctoral opportunities at the School of Physics, University College Dublin, Ireland.

Bio-Interface project is going to develop predictive models for functionality and biocompatibility of inorganic materials used in medical devices and food industry. The project uses a combination of molecular modelling and nano/bioinformatics.

On the molecular side, the work involves development of mesoscale models of biomolecules and inorganic surfaces, evaluation of interaction between them and adsorption kinetics. Once the interaction descriptors are evaluated, machine learning techniques are used to relate these properties to predict the biological activity of materials, such as formation of biomolecular corona, cell uptake or change of the molecule conformation. Bio-Interface project also covers processing of food materials such as milk. The work will be done in collaboration with the existing team at UCD and with other project partners specialised in statistical modelling and informatics. The modelling will be performed using the most modern computational facilities, including GPU stations.

Candidates should have a background in computer simulation (atomistic MD, coarse-grained MD), statistical mechanics, biophysics or soft condensed matter. Programming experience is also essential. Familiarity with common molecular and ab initio computational packages is a plus.

Applicants are requested to send a motivation letter and a CV with names of potential referees to Dr. Vladimir Lobaskin () before December 31st, 2018.

Funding Notes

Two fully funded 4-year PhD positions, stipend €18k p.a., tax free, funding from Science Foundation Ireland and European Commission, starting from January 1 2019.


1. Lopez, Lobaskin, Coarse-grained model of adsorption of blood plasma proteins onto nanoparticles, J. Chem. Phys. 143, 243138 (2015)
2. Lopez, Brandt, Mirzoev, Zhurkin, Lyubartsev, Lobaskin, Multiscale modelling of bionano interface, Adv Exp Med Biol. 2017;947:173-206. doi: 10.1007/978-3-319-47754-1_7,
3. Related project webpage

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