Sort by
Refine Your Search
-
Employer
-
Field
-
The INM – Leibniz Institute for New Materials in Saarbrücken, Germany, is an internationally leading center for materials research, a scientific partner to national and international research
-
19.05.2025 Application deadline: 31.07.2025 The group “Physics of molecular and biological materials” at the University of Tübingen is searching for Post-doctoral researcher in Physics (m/f/d, E13
-
14.05.2025, Wissenschaftliches Personal We are looking for a postdoctoral fellow to join the Neuroengineering Materials (NEN) Lab at TUM. This project is funded by the ERC Starting Grant project
-
further opportunities for interdisciplinary training. For more information about the research and study program, visit: https://www.lai.fuberlin.de/en/temporalities-offuture/index.html Job description
-
Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
findings at academic venues and publish research in peer-reviewed journals Your profile # Completed university studies (PhD) in the field of Physics, Computer science, Materials science, Chemistry, or a
-
and investigation of coated and printed efficient organic solar cells using a strongly interdisciplinary approach combining chemistry, materials science, physics, mathematics, and print technology
-
molecular/condensed matter physics) and the developments on new tools in perturbation theory and in computational methods (gradient flow), including quantum computing. We look for ambitious candidates with a
-
degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural language processing (NLP), and fine-tuning techniques
-
Your Job: Synthesis and physicochemical characterization of energy materials or representative model systems Characterization of the structure of energy materials on the atomic, molecular and
-
(such as MEA) to assess the impact of disease mutations on neuronal biology Collaborate with bioengineers, material scientists, and computational biologists to leverage AI-supported analytical pipelines