Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
level equivalent to a two-year master's degree. The ideal candidate will have a background in photonics and condensed-matter physics. You should have a passion for theoretical and computational physics, a
-
27 Aug 2025 Job Information Organisation/Company Technical University Of Denmark Department DTU Electro Research Field Engineering Physics Technology » Nanotechnology Researcher Profile First Stage
-
of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical
-
-essential components of the problem, thereby reducing the size of the subproblems and accelerating the overall solution process. The second line targets the convergence issues often encountered in column
-
the project will be the development of physics enhanced data driven methods to achieve reliable prediction of residual usable life of milling tools. The approach will be validated by application to industrial
-
questions about the recruitment process, please contact HR Coordinator Mette Fisker Præstegaard, Email: mfp@au.dk Place of work Department of Political Science, Bartholins Allé 7, 8000 Aarhus Formal
-
and Surface Engineering is multi-disciplinary and covers materials science, chemistry, physics, solid mechanics, and manufacturing technology. Properties and performance are evaluated by mechanical
-
algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
-
Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) You can learn more about the recruitment process here . Applications received after the deadline will not be
-
recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery