Forwarded from Computational and Quantum Chemistry
🚨 PhD Position in Machine Learning for Orbital-Free Density Functional Theory 🚨
📍 Heidelberg University, Germany
The Institute for Theoretical Physics (ITP) and the Interdisciplinary Center for Scientific Computing (IWR) invite applications for a PhD position in physics, focusing on orbital-free density functional theory (OF-DFT) using machine-learned functionals.
🔬 Research Focus:
Orbital-free density functional theory offers computational accuracy comparable to coupled-cluster methods but at significantly lower computational cost. Currently, precise density functionals are limited, especially for open-shell systems. This project will implement and extend an existing codebase using machine learning techniques to develop high-quality functionals for open-shell systems.
👩💻 Candidate Profile:
- Background in Physics, Chemistry, or Computer Science
- Familiarity with condensed matter physics or theoretical chemistry
- Strong programming skills (Python, C, and Torch preferred)
- Motivation for collaborative, interdisciplinary research
👥 Supervisors:
- Prof. Maurits W. Haverkort (ITP)
- Prof. Fred Hamprecht (IWR)
📧 Apply by: April 30, 2025
Send applications to:
👉 [email protected]
Don't miss this exciting research opportunity!
#PhD #MachineLearning #Physics #Chemistry #DensityFunctionalTheory #OFDFT #HeidelbergUniversity #ResearchOpportunity
📍 Heidelberg University, Germany
The Institute for Theoretical Physics (ITP) and the Interdisciplinary Center for Scientific Computing (IWR) invite applications for a PhD position in physics, focusing on orbital-free density functional theory (OF-DFT) using machine-learned functionals.
🔬 Research Focus:
Orbital-free density functional theory offers computational accuracy comparable to coupled-cluster methods but at significantly lower computational cost. Currently, precise density functionals are limited, especially for open-shell systems. This project will implement and extend an existing codebase using machine learning techniques to develop high-quality functionals for open-shell systems.
👩💻 Candidate Profile:
- Background in Physics, Chemistry, or Computer Science
- Familiarity with condensed matter physics or theoretical chemistry
- Strong programming skills (Python, C, and Torch preferred)
- Motivation for collaborative, interdisciplinary research
👥 Supervisors:
- Prof. Maurits W. Haverkort (ITP)
- Prof. Fred Hamprecht (IWR)
📧 Apply by: April 30, 2025
Send applications to:
👉 [email protected]
Don't miss this exciting research opportunity!
#PhD #MachineLearning #Physics #Chemistry #DensityFunctionalTheory #OFDFT #HeidelbergUniversity #ResearchOpportunity