Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Forschungszentrum Jülich
- National Renewable Energy Laboratory NREL
- Swinburne University of Technology
- Tilburg University
- Universidade de Coimbra
- University of Oxford;
- ;
- Loyola University
- National Research Council Canada
- Princeton University
- Queensland University of Technology
- The University of Auckland
- University of Arkansas
- University of Oklahoma
- University of Oxford
- 5 more »
- « less
-
Field
-
recently completed a pilot study investigating the use of atmospheric pressure ionisation mass spectrometry coupled with machine learning for differentiating between brain tumours and normal tissue
-
Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired
-
descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
-
Posting Title Graduate PhD Student (Year-Round) Machine Learning Applications for Cyber-Physical Power System Operations Intern . Location CO - Golden . Position Type Intern (Fixed Term) . Hours Per
-
the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
-
Supervisor: Professor Fernanda Duarte Start date: 1st October 2026 Applications are invited for a fully-funded DPhil studentship in Machine Learning Interatomic Potentials for Metal-Ligand
-
. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning. Your tasks: Development and comparison of data driven models for the prediction of stresses in
-
heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
-
this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
-
Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the