Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- Justus Liebig University Giessen •
- AALTO UNIVERSITY
- Eindhoven University of Technology (TU/e)
- Inria, the French national research institute for the digital sciences
- Institute of Neuroscience and physiology, Sahlgrenska Academy, university of Gothenburg
- Linköping University
- Monash University
- Oak Ridge National Laboratory
- Queensland University of Technology
- Technical University of Denmark (DTU)
- University of Birmingham
- University of South Carolina
- University of Surrey
- 3 more »
- « less
-
Field
-
particular emphasis on time-dependent density-functional theory (TDDFT). Understanding how electrons evolve in time is central to modern science and technology, from photochemistry and catalysis to quantum
-
Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
and D. J. C. Mackay, “Low density parity check codes over GF(q)”, Information Theory Workshop, 1998, pp. 70-71. [11] D. Declercq and M. Fossorier, “Decoding algorithms for nonbinary LDPC codes over GF(q
-
dynamics, and density functional theory (DFT) can be combined to accelerate the discovery and design of next-generation organic semiconductor materials with tailored optoelectronic properties. The project
-
standard simulation methods. This PhD topic falls within the area of computational materials science and will involve the use of established methods such as density functional theory and molecular dynamics
-
training in first-principles electronic-structure and excited-state methods (density functional theory and the GW and Bethe-Salpeter-Equation approaches), machine learning for atomistic simulation, and high
-
Institute of Neuroscience and physiology, Sahlgrenska Academy, university of Gothenburg | Sweden | 23 days ago
employees make the university a large and inspiring place to work and study. Strong research and attractive study programmes attract researchers and students from around the world. With new knowledge and new
-
Nuclear energy-density functionals are among the most powerful theoretical tools for describing atomic nuclei and for connecting laboratory nuclear physics with the properties of dense matter in
-
made significant progress in this direction by merging machine learning interatomic potentials (MLIPs) trained on density functional theory (DFT) data, and enhanced sampling techniques to reach the
-
motor concepts and provide technical leadership for research initiatives focused on high power density, efficiency, reliability, manufacturability, thermal performance, and reduced reliance on critical
-
controlling electrochemical interfaces across scales. Computational PhD position: You will develop an AI-enhanced multiscale modelling framework combining density functional theory, ab initio molecular dynamics