Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- CNRS
- Argonne
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- University of North Carolina at Chapel Hill
- Nature Careers
- VIN UNIVERSITY
- IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava
- Umeå University
- Utrecht University
- Aarhus University
- Brookhaven National Laboratory
- Chalmers University of Technology
- Oak Ridge National Laboratory
- Princeton University
- SciLifeLab
- The University of North Carolina at Chapel Hill
- Uppsala universitet
- Duke University
- ETH Zürich
- Forschungszentrum Jülich
- Fudan University
- Ghent University
- Institut Català de Nanociència i Nanotecnologia
- Iowa State University
- Jerzy Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences
- Jozef Stefan Institute
- KTH Royal Institute of Technology
- Lawrence Berkeley National Laboratory
- Luxembourg Institute of Science and Technology
- New York University
- Rice University
- Technical University of Denmark
- University of Amsterdam (UvA)
- University of California
- University of California, Merced
- University of Miami
- University of Minnesota
- University of New Hampshire – Main Campus
- University of New South Wales
- University of Southern Denmark
- University of Sydney
- University of Texas at Dallas
- University of Texas at Tyler
- Université de Bordeaux / University of Bordeaux
- VIB
- 35 more »
- « less
-
Field
-
structural models and compute electronic and vibrational properties. Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations
-
characterization with advanced computational chemistry tools, including molecular dynamics, density functional theory and Grand Canonical Monte Carlo simulations. Position Requirements A recent or soon-to-be
-
comprehensive simulation open-source codes. Experience in data analysis and simulations of complex and coupled nuclear engineering problems, using techniques such as (but not limited to) molecular dynamics
-
of scientific AI. Focus Areas: Cross-Domain Interoperability: Develop common readiness templates, standardized metadata models, and APIs to enable seamless integration across diverse scientific domains
-
molecular dynamics simulations, applicable to materials science, biomolecules, or a related field. Programming experience (e.g., Python), with a strong background in developing and applying computational
-
experience in one or more of the following NMR domains: Coding, modifying, and executing pulse sequences Simulating NMR spectra or phenomena Molecular simulations (molecular dynamics) based on NMR data Model
-
immunostaining of cells and tissues, and develops various tools for bioimage analysis, mostly using machine learning and AI-based models. As a postdoc you will conduct research using various methods in cell-and
-
statistical inference Familiarity with random simulations Demonstrated interest in the dynamics of biological systems Essential Functions: Conduct mathematical, computational, and statistical analyses of models
-
Healthcare Monitoring We welcome applications from those with expertise in or across these disciplines: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale
-
: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis