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Minimum Qualifications: Ph.D. in Materials Science, Physics, Chemistry, Mechanical Engineering, or related fields Preferred Qualifications: Strong expertise in atomic-scale simulations (e.g., MD, DFT, ML-FF
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chemistry, electronic structure (static and dynamic aspects), wave function methods (Coupled Cluster, multi-configurational methods, DMRG), Quantum Monte Carlo, DFT-type methods, Green's function methods
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research group is associated with the newly established Center of Excellence in Neutron-Star Physics (https://neutronstars.fi ), providing us long-term funding, strong connections to related Finnish and
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. Interpretation of experimental results and integration with theoretical/DFT insights in collaboration with computational partners. Active participation in synchrotron beamtime experiments (XANES, EXAFS) and post
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by computational tools (e.g., DFT) to understand and refine selective binding mechanisms. Research activities are based at LUT’s Lappeenranta campus, engaging in practical laboratory activities and
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hydrogen generation, using density functional theory (DFT) and its time-dependent extension (TDDFT). 2. In silico design and characterization of new photosensitizers for green hydrogen generation, using
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, or chemical physics. Candidates with expertise in density functional theory (DFT) or theoretical spectroscopy are particularly encouraged to apply. 4 selected references: A. Sasukimar et al
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methods to simulate between functional chemically active surfaces and molecules/liquids. Central methodologies include: static DFT calculations; TBMD and AIMD; classical atomistic and coarse-grained
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using machine learning and state-of-the-art DFT and DFPT code-packages. The project will be performed in close collaboration with various research groups in the UK and USA. Research and performing
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a Postdoctoral Fellow to contribute to building computational