Sort by
Refine Your Search
-
using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering
-
processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
-
microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments
-
THE FIELDS OF: ATMOSPHERIC PHYSICS AND CHEMISTRY, ELECTROCHEMISTRY, ELECTROCHEMICAL ENERGY STORAGE (BATTERIES), ELECTRONICS, ELECTRICAL AND MECHANICAL ENGINEERING, HIGH-PERFORMANCE COMPUTING, MACHINE LEARNING
-
, the details of the process are not yet fully understood. Mechanistic learning, the combination of mathematical mechanistic modelling and machine learning, enables a data-driven investigation of the processes
-
machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
-
using X-ray and neutron scattering. The main research areas are materials for photovoltaics, proteins in solutions and at the interfaces, complex nano-structured materials and machine learning tools
-
simulation environments, numerical methods, or machine learning approaches is an advantage Fluent command of written and spoken English is necessary; German is an advantage but not required High degree
-
Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
-
protein structure analysis. Required skills: High motivation, curiosity, self-driven, critical thinking, strong team-player, good English, high interest in protein structure and machine learning. This PhD