Vladimir graduated from Lomonosov Moscow State University in 2007, where he received his PhD degree in 2010 in the field of Statistical and Polymer Physics studying phase transition phenomena in copolymer and polyelectrolyte systems. Later he moved to work on optimisation problems in systems with anomalous diffusion at the Technical University of Munich and University of Potsdam in Germany. The mail focus of the work was target search optimisation, first-passage and first-hitting properties. Before moving to Skoltech Vladimir worked at the University of Cambridge, UK developing a framework for prediction of mechanical properties of amorphous polymers from their microscopic structure. Vladimir has authored about 20 papers in peer-reviewed journals including a few of highly cited review papers and papers in the top journals like PNAS. During his work in Munich and Cambridge he actively participated in teaching of statistical physics and maths courses.
As a faculty member, Prof. V.V. Palyulin provides teaching at graduate level, advising student and innovation projects, and conducting application-oriented research.
His current research interests include various fields of statistical physics and stochastic processes research such as trajectory analysis, reinforcement learning for target search, anomalous diffusion and crowding problems.
1. Palyulin V.V., Chechkin A.V., Metzler R., “Levy flights do not always optimize random blind search for sparse targets”, Proc. Natl. Acad. Sci. USA, 2014, 111, 2931-2936
2. Palyulin V.V., Blackburn G., Lomholt M.A., Watkins N.W., Metzler R., Klages R., Chechkin A.V., “First-passage and first-hitting of Levy flights and Levy walks”, New J. Phys., 2019, 21, 103028.
3. Palyulin V.V., Ala-Nissila T., Metzler R., “Polymer translocation: the first two decades and the recent diversification”, Soft Matter, 2014, 10, 9016-9037
4. Palyulin V.V., Ness C., Milkus R., Elder R.M., Sirk T., and Zaccone A., “Parameter-free predictions of the viscoelastic response of glassy polymers from non-affine lattice dynamics”, Soft Matter, 2018, 14, 8475-8482
5. Palyulin V.V., Chechkin A.V., Klages R., Metzler R., “Search reliability and search efficiency of combined Levy-Brownian motion”, J. Phys. A, Math. Theor., 2016, 49, 394002
List of papers Smirnov, A.M., Golinskaya, A.D., Kotin, P.A. ,Dorofeev, S.G., Zharkova, E.V., Palyulin, V.V. , Mantsevich, V.N., Dneprovskii, V.S., “Damping of Cu-Associated Photoluminescence and Formation of Induced Absorption in Heavily Cu-Doped CdSe Quantum Dots”, J. Phys. Chem. C, 2019, accepted for publication, DOI: http://dx.doi.org/10.1021/acs.jpcc.9b09918  Palyulin V.V., Blackburn G., Lomholt M.A., Watkins N.W., Metzler R., Klages R., Chechkin A.V., “First-passage and first-hitting of Levy flights and Levy walks”, New J. Phys., 2019, 21, 103028.  Smirnov, A. M., Golinskaya, A. D., Kotin, P. A., Dorofeev, S. G., Palyulin, V. V., Mantsevich, V. N., Dneprovskii, V. S., “Photoluminescence and nonlinear transmission of Cu-doped CdSe quantum dots”, Journal of Luminescence, 2019, 213, 29–35.
 Palyulin V.V., Ness C., Milkus R., Elder R.M., Sirk T., and Zaccone A., “Parameter-free predictions of the viscoelastic response of glassy polymers from non-affine lattice dynamics”, Soft Matter, 2018, 14, 8475-8482  Milkus R., Ness C., Palyulin V.V., Weber J., Lapkin A., and Zaccone A., Interpretation of the vibrational spectra of glassy polymers using coarse-grained simulations, Macromolecules, 2018, 51, 1559-1572  Ness C., Milkus R., Elder R.M., Sirk T., and Zaccone A., Nonmonotonic dependence of polymer glass mechanical response on chain bending stiffness, Phys. Rev. E (Rapid Communications), 2017, 96, 030501  Palyulin V.V., Mantsevich V.N., Klages R., Metzler R., Chechkin A.V., Comparison of pure and combined search strategies for single and multiple targets, Eur. Phys. J. B, 2017, 90, 170  Palyulin V.V., Chechkin A.V., Klages R., Metzler R., Search reliability and search efficiency of combined L´evy-Brownian motion, J. Phys. A, Math. Theor., 2016, 49, 394002  Goeppel T., Palyulin V.V., Gerland U., The efficiency of driving chemical reactions by a physical non-equilibrium is kinetically controlled, Phys. Chem. Chem. Phys., 2016, 18, 20135  Palyulin V.V., Chechkin A.V., Metzler R., Space-fractional Fokker-Planck equation and optimization of random search processes in the presence of an external bias, J. Stat. Mech., 2014, P11031  Palyulin V.V., Ala-Nissila T., Metzler R.,Polymer translocation: the first two decades and the recent diversification, Soft Matter, 2014, 10, 9016-9037  Palyulin V.V., Metzler R., Speeding up the first-passage for subdiffusion by introducing a finite potential barrier, J. Phys. A: Math. Theor., 2014, 47, 032002  Palyulin V.V., Chechkin A.V., Metzler R., Levy flights do not always optimize random blind search for sparse targets, Proc. Natl. Acad. Sci. USA, 2014, 111, 2931-2936  Palyulin V.V., Metzler R., How a finite potential barrier decreases the mean first-passage time, J. Stat. Mech., 2012, L03001  Popov K.I., Palyulin V.V., Moeller M., Khokhlov A.R., Potemkin I.I., Surface induced self-organization of comb-like macromolecules, Beilstein J. Nanotechnol., 2011, 2, 569  Yang D.A., Venev S.V., Palyulin V.V., Potemkin I.I., Nematic ordering of rigid rod polyelectrolytes induced by electrostatic interactions: Effect of discrete charge distribution along the chain, J Chem Phys, 2011, 134, 074901  Potemkin I.I., Palyulin V.V., Complexation of oppositely charged polyelectrolytes: Effect of discrete charge distribution along the chain, Phys. Rev. E, 2010, 81, 041802  Potemkin I.I., Palyulin V.V., Comblike macromolecules, Polymer Science, Ser. A, 2009, 51, 123-149  Palyulin V.V., Potemkin I.I., Mixed versus ordinary micelles in the dilute solution of AB and BC diblock copolymers, Macromolecules, 2008, 41, 4459-4463  Palyulin V.V., Potemkin I.I., Microphase separation of double-grafted copolymers (centipedes) with gradient, random, and regular sequence of the branch points, J Chem Phys, 2007, 127, 124903  Palyulin V.V., Potemkin I.I., Microphase separation in melts of double comb copolymers, Polymer Science, Ser. A, 2007, 49, 473-481
Research scientist position available in Statistical Physics and Machine Learning Group — Skoltech
Skolkovo Institute of Science and Technology (Skoltech) is a unique English-speaking international research university, located just outside of Moscow. Established in collaboration with M.I.T., Skoltech integrates and modernises the best Russian scientific traditions.
A two-year research scientist position with a possibility of a one year extension is being offered to work in Skoltech’s Statistical Physics and Machine Learning Group — led by Prof. Vladimir Palyulin.
The main project will focus on the implementation of machine learning methods for study of active matter. This includes search optimisation in complex systems and on complex networks, collective motion of active particles and anomalous diffusion properties.
An ideal candidate will have a PhD with research experience in statistical physics and/or machine learning methods. The monthly salary ranges between 140k RUB (70 RUB = 1 Euro) and 180k RUB depending on the experience. Medical insurance and partial costs of accommodation as well as moving costs can also be covered. Desired start dates are between January and March 2020.Review of applications will continue until the position is filled. Inquiries about this position and applications should be directed to Prof. Vladimir Palyulin via V.Palyulin@skoltech.ru
- Stochastic Methods in Mathematical Modelling, Term 4
Syllabus can be found here, http://files.skoltech.ru/data/edu/syllabuses/2019/MA03363.pdf