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Postdoctoral positions available in DFTQSG @ NIS ... (No replies)

dftqsg
11 months ago
dftqsg 11 months ago
The Density Functional Theory & Quantum Simulations Group (DFTQSG) (more info: http://www.niser.ac.in/~psamal/) at the Natiinal Institute of Science Education and Research (NISER), Bhubaneswar, India is working on developments of first principle density functional formalism and potentially challenging and cutting edge applications employing the same. Our primary research focus is based on methodological developments of DFT such as: construction of kinetic as well as exchange-correlation functionals in three-dimensions, 2D DFT, development of the Pseudo-potential approaches for meta-GGA functionals, applying meta-GGA range-separated functionals in the time-dependent DFT, TDDFT applied to molecules and solids with meta-GGA kernels, implementation of meta-GGA range-separated hybrid functionals in the all-electron codes, development of dielectric dependent meta-GGA level range-separated hybrid functionals, machine learning in DFT, quantum embedding, and study of the meta-GGA level hybrid functionals in the prediction of excited state properties. We are also working on DFT, DFPT, OFDFT & DMFT aided many-body techniques for addressing strongly correlated phenomena and strictly interacting electrons. Currently, we are working in close collaboration with some of multidisciplinary  experimental research groups. 
 
We are looking for interested and potential candidates for filling postdoc positions in the form of 
 
National Postdoctoral Fellowship (NPDF)
 
https://serbonline.in/SERB/npdf (Application deadline August 10, 2023)
 

DST National Postdoctoral Fellowship in Nano Science and Technology

 
https://www.jncasr.ac.in/announcements/advertisement-dst-national-postdoctoral-fellowship-nano-science-and-technology
 

Interested candidates for getting absorbed as the above mentioned postdoctoral fellows  can directly write to the mentor of the DFTQSG, Prof. Prasanjit Samal ([email protected]) with suitable multidisciplinary research projects if any.

Desired Qualifications

  • Ph.D. in Physics, Materials Science, Chemistry or any related field in Engineering. 
  • Expertise in DFT and allied theoretical and computational materials science.
  • Proficiency in the use of density functional theory simulations, applications, modelling and the development of computational methods in materials science.
  • Familiarity with machine learning DFT applications in materials science.
  • Strong record of peer-reviewed publications.
  • Excellent communication skills.
 
 



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Ab initio (from electronic structure) calculation of complex processes in materials