24 condition-monitoring-machine-learning Postdoctoral positions at Chalmers University of Technology
Sort by
Refine Your Search
-
foundational and applied topics in computer vision and machine learning, with particular strengths in inverse problems, generative models, and geometric deep learning. We work across diverse application areas
-
, computational materials science, computer science, or a related field, awarded no more than three years prior to the application deadline*. Background in physics-based battery modelling and/or machine learning is
-
computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
-
fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
-
postdoctoral position in data analysis, where you will apply machine learning techniques to understand how resistance genes spread and to help detect infections caused by resistant bacteria. The position is part
-
-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
-
passive and active flow control algorithms, potentially incorporating machine learning/AI, to enhance aerodynamic performance and stall delay with rapid response times. The research is conducted in
-
interdisciplinary and to learn new skills and to perform research in collaboration with others. We seek candidates with the following qualifications: A doctoral degree in a Bioscience-related field awarded
-
conducted in a chamber with optical access, where hydrogen-air mixtures of varying homogeneity and flow conditions will be studied at elevated pressures and temperatures. Ignition and flame properties will be
-
commitment to lifelong learning. The department emphasizes strong collaboration between academia, industry, and society, with a clear focus on utilisation. M2 is characterised by an international environment