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Nishamol Kuriakose

Bilete av Nishamol Kuriakose
Besøksadresse Moltke Moes vei 30-32 Georg Morgenstiernes hus 0851 Oslo
Postadresse Postboks 1082 Blindern 0317 Oslo
Andre tilknytingar Hylleraas-senteret

Faglige interesser

DFT studies, Small Molecule Activation, Homogeneous and Heterogeneous Catalysis, and Machine Learning

Bakgrunn

Ph.D. in Chemical Science, CSIR-National Chemical Laboratory Pune, India

M. Sc. Chemistry, University of Kerala, India

B. Sc. Chemistry, Mahatma Gandhi University, Kerala, India

Priser

PBC “Study in Israel” Fellowship

Verv

  • PBC Post-doctoral Research Fellow, The Institute of Chemistry, The Hebrew University of Jerusalem, Israel
  • Research Associate, Department of Physics, Indian Institutes of Science Education and Research (IISER) Pune, India
  • Research Scientist, A*STAR-Institute of High-Performance Computing (IHPC), Singapore
  • Postdoctoral Resarch Fellow.
    Fukui Institute for Fundamental Chemistry (FIFC), Kyoto University, Japan

 

Emneord: SMN

Publikasjonar

  • Geetha, Durga; Hameeda, B. A. Aysha; Jose, Deepthi; Kuriakose, Nishamol & Skaria, Tom (2025). Novel Insights Into the Dynamic Conformational Transitions and Active Site Plasticity of Human Immunoregulatory Cathepsin S. Proteins: Structure, Function, and Bioinformatics. ISSN 0887-3585. doi: 10.1002/prot.26845. Fulltekst i vitenarkiv
  • Puthiyottil, Shahid; Jose, Deepthi; Kuriakose, Nishamol & Skaria, Tom (2025). The developmental and inflammatory disease target protein ADAM17 is vulnerable to off-target interaction by the drug eltrombopag: Insights from molecular modeling. Computers in Biology and Medicine. ISSN 0010-4825. 186. doi: 10.1016/j.compbiomed.2025.109693. Fulltekst i vitenarkiv
  • Kuriakose, Nishamol & Shaik, Sason (2023). Oriented External Electric-Field Effects on the Activation of Aryl CO Bond in Anisole using Rh(PEP) (E=Al, B, Ga) Catalysts. Chemistry - A European Journal. ISSN 0947-6539. 29(49). doi: 10.1002/chem.202300977. Fulltekst i vitenarkiv

Sjå alle arbeida i NVA

  • Kuriakose, Nishamol (2023). Molecular Modelling and Machine Learning-Based Prediction of MOF Materials for Hydrogen Adsorption. Fulltekst i vitenarkiv

Sjå alle arbeida i NVA

Publisert 17. nov. 2022 09:39 - Sist endra 13. mars 2026 15:54